452 AI Evangelist jobs in Singapore

This role offers the opportunity to work on cutting-edge Data/AI/ML technologies and contribute to transformative business solutions in a dynamic and collaborative MNC environment.

Job Responsibilities:

• Design, develop, and optimize machine learning (ML) models and algorithms to address business challenges.
• Collaborate with cross-functional teams to gather requirements, define objectives, and deploy models effectively.
• Train and fine-tune ML models using appropriate algorithms, techniques, and tools.
• Conduct evaluations to assess model performance, applying methods such as cross-validation, hyperparameter tuning, and ensemble learning.
• Work closely with software engineers and DevOps teams to deploy models in production environments.
• Implement APIs and integrate models into existing systems to enable real-time decision-making.
• Monitor deployed models to ensure optimal performance, address anomalies, and resolve issues.
• Continuously refine models and algorithms based on user feedback and performance metrics.
• Perform exploratory data analysis to uncover trends and insights.
• Use statistical methods and visualization techniques to communicate findings to stakeholders.
• Stay updated on advancements in ML and artificial intelligence (AI).
• Evaluate and recommend new tools, libraries, and methodologies to enhance workflows.

Job Requirements:

• Min. Bachelor's Degree in Computer Science, Data Science, Statistics, Machine Learning, or a related field.
• At least 4 years of hands-on experience in designing, developing, and deploying ML models for real-world applications.
• Familiarity with Large Language Models and Generative AI technologies is a plus.
• Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Strong understanding of statistical analysis, probability theory, and hypothesis testing.
• Experience with cloud-based ML tools (e.g., AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark) is advantageous.
• Excellent communication skills to articulate technical concepts to diverse stakeholders.

Your recruiter for this job: WhatsApp Celine @ 6421 4966 for a quicker response.

Connect with me on LinkedIn:

Celine Chan | R21103433

Talentsis Pte Ltd | EA No: 20C0312

This role offers the opportunity to work on cutting-edge Data/AI/ML technologies and contribute to transformative business solutions in a dynamic and collaborative MNC environment.

Job Responsibilities:

• Design, develop, and optimize machine learning (ML) models and algorithms to address business challenges.
• Collaborate with cross-functional teams to gather requirements, define objectives, and deploy models effectively.
• Train and fine-tune ML models using appropriate algorithms, techniques, and tools.
• Conduct evaluations to assess model performance, applying methods such as cross-validation, hyperparameter tuning, and ensemble learning.
• Work closely with software engineers and DevOps teams to deploy models in production environments.
• Implement APIs and integrate models into existing systems to enable real-time decision-making.
• Monitor deployed models to ensure optimal performance, address anomalies, and resolve issues.
• Continuously refine models and algorithms based on user feedback and performance metrics.
• Perform exploratory data analysis to uncover trends and insights.
• Use statistical methods and visualization techniques to communicate findings to stakeholders.
• Stay updated on advancements in ML and artificial intelligence (AI).
• Evaluate and recommend new tools, libraries, and methodologies to enhance workflows.

Job Requirements:

• Min. Bachelor's Degree in Computer Science, Data Science, Statistics, Machine Learning, or a related field.
• At least 4 years of hands-on experience in designing, developing, and deploying ML models for real-world applications.
• Familiarity with Large Language Models and Generative AI technologies is a plus.
• Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Strong understanding of statistical analysis, probability theory, and hypothesis testing.
• Experience with cloud-based ML tools (e.g., AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark) is advantageous.
• Excellent communication skills to articulate technical concepts to diverse stakeholders.

Your recruiter for this job: WhatsApp Celine @ 6421 4966 for a quicker response.

Connect with me on LinkedIn:

Celine Chan | R21103433

Talentsis Pte Ltd | EA No: 20C0312

Join to apply for the
Artificial Intelligence/Machine Learning Modeller- Global Markets
role at
Barclays
Join to apply for the
Artificial Intelligence/Machine Learning Modeller- Global Markets
role at
Barclays
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Join the Barclays Global Markets in Singapore as an AI/ML Modeller where you’ll play a crucial role in building an AI/ML team and we’re doing it with start-up energy: lean, collaborative, and relentlessly focused on impact. We’re looking for technically exceptional, intellectually curious individuals who thrive on solving complex problems with elegant, practical solutions. You’ll help shape a greenfield function, designing and deploying models that drive innovation across trading and distribution. You’ll be assessed on your ability to think strategically, manage risk, and deliver high-quality, scalable solutions. But above all, we value curiosity, creativity, and a willingness to challenge the status quo. You will be responsible to build and productionize Machine Learning models across asset classes, apply advanced techniques in Machine Learning, statistics, and applied mathematics using Python (PyTorch or similar) and work hands-on with cloud platforms like AWS SageMaker to scale solutions fast.
This Role Requires These Essential Skills/ Qualifications
Master’s degree in a Science, Technology, Engineering and Mathematics (STEM) field (PhD preferred).
A proven record of a strong foundation in Machine Learning, data science, and software engineering.
Demonstrated success and passion for crafting solutions that are both technically rigorous and operationally effective.
Champions a collaborative mindset and a drive to learn, iterate, and improve.
Publications or open-source contributions? Even better—we value original thinking.
Desirable Skills And Qualifications
Experience in quant trading (especially eFX) or alpha research.
Natural Language Processing (NLP) and Large Language Models (LLM) expertise.
Familiarity with vector databases, SQL/NoSQL, and Amazon Bedrock.
You may be assessed on key critical skills relevant for success in the role such as mathematics, finance, programming, risk and controls, change and transformation, business acumen, and strategic thinking.
Barclays is required by law to confirm that you have the Legal Right to Work in any role that you apply for. If you currently hold a work visa sponsored by Barclays, or you would require sponsorship from Barclays, you must declare this as part of your application. Sponsored visas are role and entity specific, and any changes must be reviewed. It is important that you ensure you are working on the correct visa at all times. Failure to accurately disclose your visa status or Legal Right to Work may result in your application or any employment offer being withdrawn at any time.
Purpose of the role
To provide quantitative and analytical expertise to support trading strategies, risk management, and decision-making within the investment banking domain, applying quantitative analysis, mathematical modelling, and technology to optimise trading and investment opportunities.
Accountabilities
Development and implementation of quantitative models and strategies to derive insight into market trends and optimize trading decisions, pricing, and risk management across various financial products and markets.
Working closely with sales teams to identify clients' needs and develop customised solutions.
In-depth research, data analysis, and statistical modelling to derive insights into market trends, pricing, and risk dynamics.
Provide front office infrastructure support though ownership and maintenance of analytical libraries.
Provision of expertise on quantitative methodologies, technological advancements, and industry best practices to drive innovation within the trading environment.
Assistant Vice President Expectations
To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
Take ownership for managing risk and strengthening controls in relation to the work done.
Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
Influence or convince stakeholders to achieve outcomes.
All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.
Seniority level
Seniority level Mid-Senior level
Employment type
Employment type Full-time
Job function
Job function Engineering and Information Technology
Industries Banking and Financial Services
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#J-18808-Ljbffr

Join the Barclays Global Markets in Singapore as an AI/ML Modeller where you’ll play a crucial role in building an AI/ML team and we’re doing it with start-up energy: lean, collaborative, and relentlessly focused on impact. We’re looking for technically exceptional, intellectually curious individuals who thrive on solving complex problems with elegant, practical solutions. You’ll help shape a greenfield function, designing and deploying models that drive innovation across trading and distribution. You’ll be assessed on your ability to think strategically, manage risk, and deliver high-quality, scalable solutions. But above all, we value curiosity, creativity, and a willingness to challenge the status quo. You will be responsible to build and productionize Machine Learning models across asset classes, apply advanced techniques in Machine Learning, statistics, and applied mathematics using Python (PyTorch or similar) and work hands-on with cloud platforms like AWS SageMaker to scale solutions fast.
This role requires these essential skills/ qualifications:
Master’s degree in a Science, Technology, Engineering and Mathematics (STEM) field (PhD preferred).
A proven record of a strong foundation in Machine Learning, data science, and software engineering.
Demonstrated success and passion for crafting solutions that are both technically rigorous and operationally effective.
Champions a collaborative mindset and a drive to learn, iterate, and improve.
Publications or open-source contributions? Even better—we value original thinking.
Desirable skills and qualifications
Experience in quant trading (especially eFX) or alpha research.
Natural Language Processing (NLP) and Large Language Models (LLM) expertise.
Familiarity with vector databases, SQL/NoSQL, and Amazon Bedrock.
You may be assessed on key critical skills relevant for success in the role such as mathematics, finance, programming, risk and controls, change and transformation, business acumen, and strategic thinking.
Barclays is required by law to confirm that you have the Legal Right to Work in any role that you apply for. If you currently hold a work visa sponsored by Barclays, or you would require sponsorship from Barclays, you must declare this as part of your application. Sponsored visas are role and entity specific, and any changes must be reviewed. It is important that you ensure you are working on the correct visa at all times. Failure to accurately disclose your visa status or Legal Right to Work may result in your application or any employment offer being withdrawn at any time.
Purpose of the role
To provide quantitative and analytical expertise to support trading strategies, risk management, and decision-making within the investment banking domain, applying quantitative analysis, mathematical modelling, and technology to optimise trading and investment opportunities.
Accountabilities
Development and implementation of quantitative models and strategies to derive insight into market trends and optimize trading decisions, pricing, and risk management across various financial products and markets.
Working closely with sales teams to identify clients' needs and develop customised solutions.
In-depth research, data analysis, and statistical modelling to derive insights into market trends, pricing, and risk dynamics.
Provide front office infrastructure support though ownership and maintenance of analytical libraries.
Provision of expertise on quantitative methodologies, technological advancements, and industry best practices to drive innovation within the trading environment.
Assistant Vice President Expectations
To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
Take ownership for managing risk and strengthening controls in relation to the work done.
Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
Influence or convince stakeholders to achieve outcomes.
All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.
#J-18808-Ljbffr

We are looking for a highly skilled and experienced Machine Learning Engineer to join our team and drive innovation in music and audio technology.

The ideal candidate will have a strong background in machine learning, audio signal processing, and music theory. You will conduct research on novel machine learning techniques for music and audio applications, develop and deploy these models into real-world products and services, and collaborate closely with engineers and scientists to solve complex challenges.

Your work will directly impact how users experience and interact with music technology.

• Develop and apply state-of-the-art machine learning and deep learning models to tackle challenges in music generation, source separation, audio enhancement, and music information retrieval
• Conduct research on innovative machine learning techniques tailored for music and audio applications
• Deploy machine learning solutions in production environments powering real-world products and services
• Collaborate closely with multidisciplinary teams of engineers, researchers, and product managers to solve complex problems in music and audio technology

• Master's or PhD degree in Computer Science, Machine Learning, or a related field (equivalent work experience will also be considered)
• Strong proficiency in Python programming, with hands-on experience using ML frameworks such as PyTorch and TensorFlow, and audio processing libraries like Librosa
• Solid understanding of state-of-the-art ML models and techniques
• Good understanding of basic music theories such as chords, scales, and intervals
• Familiarity with MIDI and Audio formats, including MIDI message structures and audio file formats
• Strong knowledge in digital signal processing
• Excellent problem-solving and analytical skills, with attention to detail
• Ability to work both independently and collaboratively in a fast-paced environment
• Effective communication skills and the ability to translate technical concepts to non-technical stakeholders

Preferred qualifications

• Background or strong interest in music, with knowledge of music theory and composition
• Experience in one or more areas of music AI, such as:

- Music Generation
- Source Separation
- Audio Enhancement
- Music Transcription (chords, notes)
- Singing Voice Synthesis
- Music Information Retrieval

• A strong record of first-author publications in leading AI conferences or journals (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, ICASSP)
• Proficiency in C/C++ and shell programming languages, with a deep understanding of data structures and algorithm design
• Experience with MLOps frameworks, such as MLFlow or KubeFlow

That is a lot of computing power, so why do we need it?

We’re pushing the boundaries of AI by building cutting-edge machine learning models and tools from the ground up. To support this, we’ve invested heavily in high-performance computing, including the Ahrefs Superpod, which boasts 60 nodes from 63 and scored 19.7 PFlops in Linpack, ranking it among the top 30 supercomputers in the world. Simply put, we have the infrastructure to turn ambitious ideas into reality.

For over a decade, Ahrefs has been crawling the web, processing petabytes of data, and delivering powerful insights through an intuitive interface. Now, we’re leveraging this expertise to develop innovative AI-driven solutions that help users navigate, analyze, and extract value from vast amounts of information like never before.

Let’s put that compute power to use!

In this role you’ll have the opportunity to work on cutting-edge research and turn it into real-world impact. We're looking for a dynamic Machine Learning Engineer to join us in creating cutting-edge AI products that push the boundaries of what’s possible. Bring your creativity, develop your own ideas, and see them through, from fuzzy concepts to production, all in a fast-moving, red-tape-free environment.

• Work on LLMs and other AI models, spanning training, fine-tuning, inference optimization, and new architectures.
• Algorithm Research & Development
  • Design and implement algorithms for search, agents, knowledge retrieval, and generative AI applications.
• Stay on the Cutting Edge
  • Stay ahead of NLP and RL advancements, evaluate emerging models/frameworks (e.g., SSMs, text diffusion), and assess their impact on our products.
• Scaling & Optimization
  • Optimize model inference, reduce latency, and improve efficiency using techniques like distillation, quantization, and tensor parallelism.
• Collaborate with Engineering & Product Teams
  • Work closely with engineering and product teams to ship AI-driven features at scale.

• Experience with modern deep learning frameworks (e.g., PyTorch, JAX).
• Familiarity with transformer-based architectures and techniques (e.g. flash attention, speculative decoding, KV caching).
• Strong software engineering skills (Python, CUDA, or C++ a plus).
• Interest in one or more areas: large-scale training, agentic workflows, inference optimization, retrieval-augmented generation (RAG), reinforcement learning (RLHF/RL), or multimodal AI.
• Experience with distributed training and model deployment libraries (e.g. Megatron, Ray, Triton (both or either!), vLLM) is a bonus.

You’ll have opportunities to work on projects at the cutting edge of AI. You’ll get the chance to shape the future of our product and make a real impact.

If you're a Machine Learning Engineer with the drive to turn research into reality, we'd love to hear from you! Join us and be part of a team that's pushing the boundaries of technology and innovation.

Our data science team faces a big, exciting challenge: building machine learning models to improve the Fairsearch experience. What a user wants to see when they run a search, and what makes a piece of content better or more relevant than another – these are vital questions that inform how we rerank web pages. Sounds interesting? We'd love to hear from you.

Our motto is first do it, then do it right, then do it better.

Viridien ( ) is an advanced technology, digital and Earth data company that pushes the boundaries of science for a more prosperous and sustainable future. With our ingenuity, drive and deep curiosity we discover new insights, innovations, and solutions that efficiently and responsibly resolve complex natural resource, digital, energy transition and infrastructure challenges.

Job Summary

We’re seeking a versatile Machine Learning Engineer with strong data engineering instincts and a passion for production-grade AI systems. You'll play a pivotal role across the AI development lifecycle — from data ingestion to deployment — ensuring our models are reliable, reproducible, and impactful.

About the Team

You’ll be joining a dynamic, globally AI team driving the application of Large Language Models (LLMs) and agentic workflows into our digital solutions. Our mission is to translate the latest advancements in AI into real business impact.

Key Responsibilities

• LLM/NLP Model Development

  • Deploy and fine tune LLMs models for domain-specific tasks.

  • Build evaluation infrastructure and benchmarking pipelines to compare model performance across multiple datasets and tasks.

• Data Infrastructure

  • Collaborate with Data Scientist to build and own data pipelines for ingestion, transformation, versioning, and labeling.

  • Ensure robust, reproducible data loops to power iterative development.

• AI Workflow Design & Orchestration

  • Orchestrate multiple models to deliver SOTA results.

  • Partner with Production team, Software Engineers to bring AI solutions into real-world products.

Qualifications:

Required:

• Degree, Master’s or Ph.D in Computer Science, Mathematics, Physics, Electrical Engineering, or other related technical disciplines.

• Passion and aptitude for programming and technology

• Enthusiasm for analytical and problem-solving challenges

• Strong enterprise project experience with Machine Learning and AI

• Strong programming skills within one or more of these development languages - C / C++ / R / Java / Python

• Good experience with Large Language Model technologies

• Experience within Data Engineering/Data Structuring

• Experience creating Machine Learning Algorithms and/or Libraries.

• Proven experience with deep learning frameworks and usage of DL libraries (TensorFlow/PyTorch)

• Ability to define and manage project deadlines and balance workloads across a wide variety of projects.

• Effective communication skills to keep all stakeholders regularly informed on progress.

• Enthusiastic attitude towards learning and flexibility to adapt to new challenges or changes in direction.

Benefits:

• 13-months Annual Base Salary and performance bonus

• Flexible Hybrid Work Model

• Comprehensive Personal and Family Healthcare

• Onsite Wellness & Recreation Corner

• Fun Employee Engagement & Sustainable Activities

• Family Leave for employees

#LI-JC

Our Hiring Process

At Viridien, we are committed to delivering a respectful, inclusive, and transparent recruitment experience.

Due to the high volume of applications we receive, we may not be able to provide individual feedback to every applicant. Only candidates whose qualifications closely match the role criteria will be contacted for an interview. We do, however, aim to share personalized feedback with those who progress to the first round of interviews and beyond.

We are also dedicated to ensuring that our hiring process accessible to all. If you require any reasonable adjustments to fully participate in the application or interview stages, please don’t hesitate to contact your recruiter directly.

We see things differently. Diversity fuels our innovation, we value the unique ways in which we differ, and we are committed to equal employment opportunities for all professionals.

About Unravel Carbon

At Unravel Carbon, we're on a mission to accelerate the world's transition to a zero-carbon economy. We're a team of entrepreneurs, engineers, and climate experts who believe that data and AI are the keys to unlocking a sustainable future. Our Sustainability AI agents platform helps companies across the globe to measure, reduce, and report their carbon emissions with unprecedented accuracy and efficiency. We're backed by top-tier investors like Sequoia and Y Combinator, and we're growing fast.

Our culture is built on a foundation of intellectual honesty, extreme ownership, and a relentless focus on results. We're a fun, collaborative, and purpose-driven team that isn't afraid to tackle the world's biggest challenges. If you're ready to do the best work of your life and make a real impact, we want to hear from you.

About The Role

We are looking for an early-career ML Engineer with a focus on Generative AI to join our early, growing team. It is a great opportunity to join a company that can have a material impact on fighting climate change.

As the Machine Learning team, we strive to design and build AI products and systems that are reliable, scalable, and maintainable. Some of the traits that we promote within the team are ownership, curiosity, transparency, and a strong writing culture. As an early team member, you will be expected to help shape our product direction and to strengthen the team's culture. You will collaborate closely with product managers, software engineers, designers, data engineers, and sustainability experts to ship products that create value and solve problems for our customers.

What You Will Work On

• Build AI agents for sustainability professionals that automate emissions calculations, extract insights from emissions inventory, generate sustainability reports, and streamline other key sustainability workflows.
• Develop LLM-powered systems that process and understand sustainability data from various sources like invoices, utility bills, and supply chain documents.
• Build agentic workflows that combine language models with structured data processing and domain-specific reasoning capabilities.
• Continuously improve our multi-ML model (semantic search and text classification) carbon engine that calculates carbon emissions, using millions of lines of transactional data and our proprietary data set of carbon emission factors.
• Design and build scalable, modular ML services on AWS infrastructure that serve both traditional ML models (transformer-based models like ModernBERT, T5) and LLM-based systems in production.
• Implement evaluation frameworks and quality controls for LLM-based systems to ensure reliable performance in production.
• Lead our efforts to build AI-powered systems that leverage our various data sets to automatically identify and recommend decarbonization solutions for our customers.

About You

• You have 1-3 years of experience in Machine Learning, Generative AI or are an upcoming new graduate with extensive relevant internships.
• You have strong experience in Python, SQL and are comfortable with modern ML frameworks like transformers, LangChain, or similar libraries.
• You are familiar with LLMs, prompt engineering, and have worked with LLM APIs or built RAG systems.
• You have shipped NLP/ML solutions to production and can demonstrate the impact of your work.
• You are able to own the entire lifecycle of a Machine Learning project. You don't need to be an expert on every aspect of it, but you must be a quick learner to pick things up and go deep when needed.
• You have an understanding of system design and can build scalable ML services.
• You like to think through product problems and enjoy working cross-functionally.
• You use solid engineering practices, write maintainable code, and care about code quality.
• You are proficient with AI-based coding tools and use them effectively in your workflow.
• You thrive in a fast-paced environment and can adapt quickly to changing priorities.
• You enjoy mentoring others where you can.

BONUS POINTS IF

• You have experience with LLM evaluation, guardrails, or agent frameworks.
• You have worked with vector databases and embedding systems.
• You have domain knowledge in sustainability, carbon accounting, or climate tech.
• You have a Master or PhD degree in Computer Science, Applied Computing, Computational Linguistics, Machine Learning or a related field.

What You’ll Gain

• Opportunity to shape product direction and team culture at a fast-growing climate tech startup backed by top-tier investors.
• Work directly with founders and senior leadership on products that have material impact on fighting climate change.
• Gain deep expertise in applying cutting-edge AI techniques to solve critical sustainability challenges.
• Experience building production AI systems at scale while contributing to the world's transition to a zero-carbon economy.

About this role

We are on the lookout for a Junior Machine Learning Engineer who will play a key role in enhancing our Machine Learning capabilities, focusing on innovative solutions for systematic strategies. This role is not just about technical expertise but also about aligning with our forward-thinking vision and being at the forefront of shaping our AI strategy.

Key Responsibilities

ML Engineering and Operations:

• Develop, implement and optimize predictive models using machine learning and deep learning / AI techniques.
• Deploy, maintain and monitor production models on AWS

ETL & Data Management:

• Design and develop efficient ETL pipelines to process and manage large volumes of financial data and alternative data.
• Ensure data integrity and accuracy across various data sources.

Cloud Computing:

• Utilize Cloud services to deploy and manage machine learning models in a scalable and reliable manner (Terraform, AWS ECS, Docker, CI/CD pipelines).
• Optimize Cloud resources for performance and cost-effectiveness.

End-to-End Solution Development:

• Engage in the complete lifecycle of model development, from data collection and preprocessing to model deployment and monitoring.

Innovation & Creativity:

• Explore and implement innovative techniques to solve complex financial problems.
• Stay current with the latest advancements in machine learning and data science to continually improve and innovate.

Result-Oriented Approach:

• Focus on delivering high-impact results.
• Communicate findings and recommendations effectively to senior stakeholders.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, AI, Statistics, Mathematics, or a related field.
• 1-3 years of hands-on experience in data science and machine learning (exposure to financial markets in a professional context in a plus).
• Proficiency in Python and relevant libraries (e.g., scikit-learn, Polars, PyTorch).
• Experience with AWS services (e.g., S3, ECS, Lambda, Athena, CloudWatch, etc.).
• Strong understanding of Data platform ETL processes and tools.
• Excellent problem-solving skills and a creative mindset.
• Strong communication and collaboration skills.