14 jobs in Keysight Technologies

Overview

Keysight Technologies’ QES division is seeking a highly skilled GUI & Full Stack Software Developer to design and develop desktop-focused graphical user interfaces (with web capability as a secondary option) supporting quantum automation, data management & analysis, and system configuration & operation.

You will collaborate across a multidisciplinary engineering environment—including physicists, firmware engineers, and backend developers—to implement intuitive user interfaces, data workflows, and backend services that power Keysight’s quantum control platform. While desktop GUI development is preferred, candidates with strong full stack experience will help extend our platform with web-compatible components, backend services, and scalable system integrations.

Responsibilities

• Design, implement, and maintain desktop GUIs for automation workflows, data visualization/analysis, instrument control, and system configuration.
• Develop full stack components—including backend services (C#, , GoLang, Node.js), APIs, and front-end web interfaces (Angular, TypeScript, WPF)—to support cross-platform tooling and integration where appropriate.
• Collaborate with users and product owners to translate complex quantum workflows into intuitive UI/UX designs, mockups, and prototypes.
• Build reusable UI and application frameworks that support long-term maintainability, extensibility, and performance.
• Integrate GUIs with hardware-control layers, quantum SDKs, and backend orchestration systems through well-defined APIs.
• Develop robust testing strategies including unit, integration, functional, and UI automation tests; work with QA to ensure system-level reliability.
• Implement data visualization and data-management interfaces for experiment results, logs, metadata, and system performance analytics.
• Contribute to architectural decisions involving UI technologies, backend frameworks, IPC/communication patterns, and deployment models.
• Participate in code reviews, design reviews, and technical discussions, ensuring consistency and quality across the team.
• Document UI workflows, software interfaces, and system interaction models.
• Collaborate effectively across multidisciplinary engineering teams, including Core OS, and Platform Engineering groups.

Qualifications

• BS/MS in Computer Science, Software Engineering, or a related technical field.
• Strong experience building desktop GUI applications (Qt, PyQt/PySide, .NET/C#, or similar frameworks).
• Proficiency in full stack development, including TypeScript, Angular (or comparable front-end frameworks), Node.js, GoLang
• Ability to design, build, and maintain RESTful APIs, backend microservices, or orchestration layers.
• Solid understanding of UI/UX principles, user workflow design, data visualization, and responsive interface patterns.
• Experience integrating front-end applications with hardware control systems, real-time data pipelines, or scientific instrumentation.
• Strong debugging and troubleshooting skills across the UI ↔ backend ↔ hardware boundary.
• Excellent verbal and written communication skills.
• Highly organized, detail-oriented, and comfortable working in a dynamic R&D environment with evolving requirements.

Preferred / Nice-to-Have:

• Experience with graphical workflows for scientific, engineering, or data acquisition systems.
• Experience designing cloud-compatible UIs or hybrid desktop/web interfaces (Electron, embedded browsers, etc.).
• Familiarity with Keysight instrumentation, PXI systems, or real-time measurement workflows.
• Understanding of quantum computing or willingness to rapidly learn quantum concepts.
• Experience with CI/CD pipelines, UI automation frameworks, or end-to-end testing systems.

This position is within the Electronic Industrial Solutions Group (EISG), where we research, innovate, develop, and manufacture the world’s most advanced manufacturing test solutions used to produce various electronic products, such as notebook motherboards, automotive ECUs, and smart meters.

As a senior Firmware Engineer, you will be an integral part of a multidisciplinary team of R&D engineers developing next-generation electrical systems and components. Your responsibilities will include:

• Designing and developing firmware and software for Keysight’s Manufacturing Test products (new product generation or existing product maintenance).
• Collaborating closely with system experts to evaluate, design, and develop measurement software to enhance test and measurement capabilities.
• Working with the project team to ensure the final product meets all regulations and customer requirements.
• Conducting experiments to test and validate new concepts, ensuring they can be effectively brought to reality.
• Owning one or multiple sub-systems and making changes in current system software/firmware to correct errors, improve quality, and add new features or performance improvements.
• Designing and performing software/firmware testing (unit tests, integration tests, etc.).
• Participating in or conducting technical reviews to identify problems early in the development phases.
• Creating detailed technical design documentation

Job Qualifications

• Recognized degree in Electrical/Electronic Engineering or Computer Science.
• Minimum of 8 years of working experience in R&D or a similar product generation environment as a firmware engineer.
• Experience and demonstrated understanding of software methodologies and good practices.
• Strong C and C++ programming skills and demonstrated structured programming experience.
• Experience with embedded operating systems (such as embedded Linux, WinCE) is a must .
• Working experience with Linux platform driver design.
• Experience using equipment like oscilloscopes and logic analyzers for problem resolution and design verification.
• Working knowledge related to low-level device driver development for peripherals like PCIe, Serial (SPI/I2C/RS485), USB, Ethernet is an added advantage.
• Good knowledge of schematics and common analog and digital components, e.g., ADC, DAC, eMMC.
• Familiarity with version control software – Git.
• Self-motivated team player with strong interpersonal skills.
• Ability to work in a cross-functional team environment.

Desired Qualifications

• Knowledge in Boundary Scan Technologies
• Familiarity with IEEE , 1500, 1687, and 1838 standards.
• Understanding of IC (Integrated Circuit) testing is an advantage.
• Working knowledge of ARM-based processors and microcontrollers such as NXP i.MX8/MK24/64, TI AM67 is an added advantage.
• Experience in Perl/Python scripting languages is an added advantage.

We are seeking a passionate and innovative application and Solution Development engineer to join our team in Electrical & Industrial Solutions Group Center of Excellence (EISG COE) to launch the next generation solution in boundary scan (JTAG, IEEE 1149) testing. Being part of the application solution development team, you will play a leading role in engaging customers to implement solutions to fulfil their requirements. You will provide guidance and drive the team towards the ideal software architecture and design for our boundary scan products.

As an Application & Solution Development Engineer, your responsibilities will include:

• Primarily to apply deep technical application and test technology expertise to develop and deliver compelling solutions to customers of the boundary scan solutions in manufacturing.
• Work as part of the product planning team to develop new solutions and technologies to address customer requirements.
• Serve as the customer advocate by thoroughly understanding their testing requirements and challenges. Collaborate with customers and R&D teams to design and implement tailored solutions, encompassing product selection and design, system setup, and testing. Develop and optimize application software in alignment with customer specifications, while integrating Keysight and third-party products and services into In-Circuit Test (ICT) systems.
• Develop and debug ICT test programs according to customer’s specifications while maximizing Keysight’s solution capabilities.
• Develop new solutions and technologies to address customer requirements as part of the product planning team.
• Research new areas to improve the testability of the customer’s products.
• Troubleshoot application anomalies on Keysight’s solutions and propose actions or solutions.
• Verifies Keysight’s solutions function per specifications and meets the customer’s needs.
• Performs competitive benchmarking and monitors industry trends.
• Provide technical support by resolving customer issues and providing consultation on use of Keysight’s solutions.
• Author customer-facing technical and application literature and multimedia content to describe key differentiators on Keysight’s solutions.
• Deliver customer training classes and consultation related to the solutions and applications.

Job Qualifications:

• Bachelor/Master Electrical/Electronic Engineering, from an accredited college or university.
• Minimum 3 years’ experience working with product development/engineering and product management.
• Knowledge of the ICT system (Keysight i3070, i1000 or any other brands) is a must.
• Knowledge of Boundary Scan (JTAG, IEEE 1149) test development and debug is a must.
• Working experience on manufacturing processes and test strategies is important.
• Strong analytical abilities.
• Self-motivated team player with strong interpersonal skills.
• Ability to work in a cross-functional team environment.

Desired Qualifications:

• Knowledge of board electronics test strategies and processes in manufacturing.
• Knowledge in x1149 Boundary Scan Technologies
• Familiarity with IEEE , 1500, 1687, and 1838 standards
• Understanding and producing board-level DFT report is an advantage

This position is within the Electronic Industrial Solutions Group (EISG), where we research, innovate, develop, and manufacture the world’s most advanced manufacturing test solutions used to produce various electronic products, such as notebook motherboards, automotive ECUs, and smart meters.

As a Research Engineer, you will play a crucial role in a multidisciplinary team of R&D engineers focused on developing next-generation electrical systems and components. Your primary focus will be on integrating advanced RF test solutions into our test systems. Your key responsibilities include:

• Conducting periodic literature reviews on the latest RF and microwave sensing technologies applicable to advanced semiconductor testing.
• Collaborating with cross-functional teams, including electrical engineers, systems engineers, and software developers, to seamlessly integrate RF test solutions into our test systems.
• Ensuring compliance with all regulations and customer requirements by working closely with the project team.
• Analyzing, designing, optimizing, and implementing RF test solutions to enhance our existing sensing capabilities.
• Developing and executing test benches for code validation and verification against models.
• Diagnosing and resolving issues related to RF hardware integration.
• Creating and maintaining detailed design documentation, including block diagrams, schematics, and layouts.

Qualifications

Educational Background:

• Bachelor's or Master’s degree in electrical engineering, Electronics Engineering, or a related field.
• Specialization or coursework in RF and Microwave Engineering is highly desirable.

Experience:

• Minimum of 3-5 years of experience in RF and microwave systems design and testing.
• Proven experience in integrating RF test solutions into complex systems.

Technical Skills:

• Strong knowledge of RF and microwave sensing technologies.
• Proficiency in using RF test equipment such as network analyzers, spectrum analyzers, and signal generators.
• Experience with RF simulation tools (e.g., HFSS, CST, ADS).
• Familiarity with semiconductor testing and related standards.
• Proficiency in programming languages such as Python, MATLAB, or C/C++ for test automation.
• Knowledge of de-embedding techniques to accurately characterize device performance by removing the effects of test fixtures.
• Experience with Time Domain Reflectometry (TDR) testing for analyzing and troubleshooting signal integrity issues in high-speed circuits.

Soft Skills:

• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities to work effectively with cross-functional teams.
• Attention to detail and a commitment to producing high-quality work.

Desired Qualifications

• Experience with advanced RF measurement techniques and tools.
• Knowledge of electromagnetic compatibility (EMC) and electromagnetic interference (EMI) testing.
• Familiarity with machine learning algorithms for RF signal processing.
• Experience in developing automated test systems.
• Strong background in signal integrity and high-frequency circuit design.

As a Senior Schematic & PCB Design Engineer in our Electronic Industrial Solutions Group (EISG), you will:

• Design and develop advanced analog and mixed-signal circuits for next-generation manufacturing test solutions.
• Experiment and innovate: Validate new concepts and bring them to life, driving improvements in test coverage and accuracy.
• Ensure compliance: Collaborate to meet regulatory and customer requirements.
• Prove feasibility: Create and document electrical structures that meet ambitious design goals.
• Analyze and evaluate: Refine hardware designs to ensure robustness and reliability.
• Integrate and modify: Support instrument/system integration and deliver tested, functional hardware.
• Document thoroughly: Prepare clear, comprehensive documentation for fabrication and production.
• Support production: Partner with manufacturing to launch new products and provide ongoing technical support.

Job Qualifications:

• Degree in Electrical & Electronics Engineering with 5+ years of relevant experience.
• Strong experience in analog circuit design and analysis, with a focus on fine-pitch PCB layouts for high-density, compact electronic systems.
• Strong experience with PCB design software (e.g., Xpedition, Altium).
• Proven track record of transferring prototypes to successful production.
• Solid understanding of material science and properties.
• Experience in complex industrial module design (EMC design is a plus).
• Excellent communication and analytical problem-solving skills.
• Flexibility, creativity, and initiative in a dynamic environment.
• Strong interpersonal and planning abilities.

Bonus Points For:

• Experience in the manufacturing test industry.
• Hands-on use of in-circuit testers, especially Keysight i3070 series.
• RF circuitry experience: Candidates with experience in RF (Radio Frequency) circuit design and analysis will be highly regarded.

We are seeking an experienced Software Development Engineer to design and build end-to-end full-stack applications, encompassing intuitive frontend user interfaces and scalable backend services. This role involves developing responsive, user-friendly UI components using modern frameworks such as React or Vue, alongside building robust backend APIs and services (REST/GraphQL) to support application logic and data processing.

You will integrate AI/ML capabilities, including large language model (LLM) APIs and other inference services, into production-ready systems, while architecting efficient data pipelines for ingestion, transformation, and storage to enable AI-driven features. The role requires optimizing performance, scalability, and reliability across the full stack, and working closely with R&D, product, and design teams to translate concepts into functional, user-facing solutions. You will operate in a fast-paced R&D environment, rapidly prototyping and iterating while maintaining high engineering standards, and contributing to architectural decisions and team mentorship.

Key Responsibilities

• Design and develop end-to-end full-stack applications, including frontend interfaces and backend services
• Build responsive, high-performance UIs using modern frameworks (e.g., React, Vue)
• Develop and maintain scalable backend systems and APIs (REST/GraphQL)
• Integrate and operationalize AI/ML capabilities (e.g., LLM APIs, inference services) into production systems
• Architect and implement data pipelines for AI-driven applications
• Ensure performance, scalability, and reliability across frontend and backend systems
• Collaborate with cross-functional teams to deliver user-facing features
• Rapidly prototype and iterate on new ideas in an R&D environment
• Implement state management, caching, and asynchronous workflows for real-time interactions
• Design and manage cloud-based infrastructure (AWS)
• Apply best practices in code quality, testing, CI/CD, and system monitoring
• Monitor, debug, and optimize production systems (logging, observability, performance tuning)
• Ensure security and data privacy in system design
• Mentor junior engineers and contribute to technical leadership

Job Qualifications

Must-Have Qualifications

• Master’s degree in Computer Science, Software Engineering, or a related field, with 5+ years of experience in full-stack software development
• Strong frontend expertise (React, Vue, or similar) and solid backend development skills (Python, Node.js, Java, or equivalent)
• Proven experience designing and building scalable APIs and systems, with strong fundamentals in system architecture and software design
• Hands-on experience integrating AI/ML services (e.g., LLM or inference APIs) into production applications
• Experience with cloud platforms (AWS) and modern development practices (version control, testing, CI/CD)
• Demonstrated experience building scalable summarization/information extraction pipelines and production-grade anomaly detection or predictive models on numerical/time-series data
• Familiarity with Agile/Scrum methodologies and rigorous validation of ML/GenAI systems (evaluation metrics, bias/risk assessment)
• Strong problem-solving skills, ability to work independently, and effective cross-functional communication
• Fluency in English, including technical communication

Strongly Preferred

• Experience building AI-powered applications involving LLMs, generative AI, or real-time inference systems
• Familiarity with ML workflows, model evaluation, and performance optimization
• Experience developing data-rich, interactive UIs (dashboards, visualizations, graphics-heavy applications)
• Hands-on experience with cloud-native architectures and containerization (Docker, Kubernetes)
• Experience with asynchronous processing, streaming systems, or real-time data pipelines
• Background in R&D or fast-paced product environments with rapid prototyping cycles
• Exposure to MLOps practices, monitoring, and observability tools
• Experience mentoring engineers or contributing to technical leadership
• Experience with Model Context Protocol (MCP) for standardized, secure integration between LLM systems and external data sources, tools, or enterprise services.

We are expanding our engineering team with a dedicated MLOps Engineer specializing in AWS to support the deployment, scaling, and operationalization of machine learning solutions across our manufacturing and semiconductor analytics platforms. This role will serve as a critical bridge between our Machine Learning Engineers—focused on Generative AI and classical ML—and production environments, ensuring seamless, reliable, and efficient ML workflows.

You will collaborate closely with the Senior Machine Learning Engineer (GenAI Platform) and the Machine Learning Engineer (Classical ML and Predictive Analytics) to automate pipelines, monitor model performance, and manage infrastructure for high-stakes applications like test plan generation, anomaly detection, predictive maintenance, and market intelligence. In our AWS-centric ecosystem, you will leverage best-in-class tools to enable rapid iteration while maintaining compliance, security, and cost efficiency in regulated industrial settings.

This position is perfect for a mid-level professional with a passion for DevOps in ML contexts, who excels at turning complex models into robust, production-ready systems.

Key Responsibilities

• Design, implement, and maintain end-to-end MLOps pipelines on AWS, including CI/CD automation for model training, validation, deployment, and retraining, using services like SageMaker, CodePipeline, CodeBuild, and Step Functions.
• Support the Generative AI platform by operationalizing AWS Bedrock workflows, including RAG pipelines, vector databases (e.g., via OpenSearch or Pinecone integrations), Lambda functions, and agentic systems—ensuring scalability for large-scale data processing like historical test plans and news article summarization.
• Enable classical ML initiatives by deploying and monitoring models built with XGBoost, Scikit-learn, and NLP architectures (e.g., RNNs/LSTMs) on AWS infrastructure, incorporating drift detection for anomaly tracking in sensor data and competitor pricing monitoring.
• Manage infrastructure as code (IaC) using Terraform or CloudFormation to provision and optimize AWS resources, such as EC2 instances, S3 buckets, EMR for Apache Spark-based processing (supporting our PMA product), and ECS/EKS for containerized deployments.
• Implement comprehensive monitoring, logging, and alerting systems with CloudWatch, X-Ray, and third-party tools (e.g., Prometheus/Grafana integrations) to track model performance, detect anomalies, handle concept drift, and ensure high availability for customer-facing tools like Q&A chatbots and predictive maintenance advisors.
• Collaborate in an Agile environment with ML engineers, data scientists, and SRE teams to conduct A/B testing, version models, automate rollbacks, and optimize costs through auto-scaling and spot instances.
• Enforce security and compliance best practices, including IAM roles, VPC configurations, data encryption, and audit logging, to safeguard sensitive manufacturing data and meet industry standards.
• Troubleshoot production issues, perform root-cause analysis, and drive continuous improvements in ML operations, staying ahead of AWS innovations to enhance platform reliability and efficiency.

Job Qualifications:

Must-have qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field.
• 3–5 years of experience in MLOps, DevOps, or cloud engineering roles, with a proven track record of deploying and managing ML models in production environments.
• Deep expertise in AWS services for ML and data workflows, including SageMaker (real-time endpoints, inference components, multi-instance/multi-variant deployments), Bedrock (provisioned throughput, cross-Region inference profiles for scaling & resilience), EMR (for Spark-based PMA workloads), Lambda, S3, ECR, and orchestration tools like Step Functions or Airflow.
• Proven experience with Amazon Elastic Container Registry (ECR): building, scanning for vulnerabilities, tagging, versioning, and pushing custom Docker images for inference containers (including Bring-Your-Own-Container patterns for custom ML frameworks, vLLM, or deep learning environments); managing ECR lifecycle policies, replication across regions, and secure access via IAM roles.
• Strong proficiency in EC2-based ML deployments and infrastructure: selecting optimal instance types (e.g., ml.g family for GPU-heavy GenAI inference, g5/g6 for newer accelerators), configuring Auto Scaling Groups, managing spot instances for cost optimization, and handling EC2 fleets for custom hosting when SageMaker/Bedrock abstractions are insufficient.
• Expertise in load balancing & scaling for ML inference: configuring and troubleshooting Application Load Balancers (ALB) or Network Load Balancers (NLB) integrated with SageMaker endpoints or ECS/EKS tasks; implementing SageMaker's built-in routing strategies (e.g., least outstanding requests for latency optimization); setting up auto-scaling policies (target tracking on CPU utilization, invocations per instance, or custom CloudWatch metrics); using cross-Region inference profiles in Bedrock for burst handling and global resilience; and ensuring high availability through multi-AZ deployments with minimum instance counts ≥2.
• Demonstrated ability to resolve common deployment issues in production ML environments, including: cold-start latency in serverless/containerized inference, container pull failures from ECR, IAM permission misconfigurations causing access denied errors, model artifact corruption or version mismatches post-deployment, endpoint update failures without downtime (using blue/green or canary strategies), drift/throttling in high-concurrency scenarios (e.g., 429 errors in Bedrock), unhealthy instance recovery, and debugging via CloudWatch Logs, X-Ray traces, and SageMaker Model Monitor alerts.
• Proficiency in IaC tools such as Terraform or CloudFormation to provision and optimize AWS resources (e.g., ECR repositories, EC2 fleets, ALBs, SageMaker endpoints, and auto-scaling configurations) in a repeatable, auditable manner.
• Strong scripting and programming skills in Python (with libraries like Boto3), along with experience in CI/CD pipelines using Jenkins, GitHub Actions, or AWS CodePipeline — with specific focus on automated ECR image builds, model artifact promotion, and safe endpoint updates.
• Familiarity with monitoring and observability stacks (e.g., CloudWatch, ELK Stack) and ML-specific tools for versioning (e.g., MLflow) and experiment tracking.
• Experience in Agile methodologies, with hands-on participation in sprints, code reviews, and cross-functional problem-solving.
• Solid understanding of ML concepts, including model drift, bias detection, and serving patterns, to effectively support both GenAI and classical ML teams.

Strongly preferred

• Fluency in English.
• Prior exposure to manufacturing, semiconductor, or industrial IoT domains, where data reliability and low-latency inference are critical.
• Certifications such as AWS Certified Machine Learning – Specialty, AWS Certified DevOps Engineer, or equivalent.
• Experience with hybrid ML setups, integrating on-premises data with cloud services, or handling large-scale NLP/Numerical data pipelines.
• Knowledge of security frameworks like SOC 2 or ISO 27001, and tools for automated testing of ML infrastructure.
• Prior experience troubleshooting and optimizing SageMaker multi-instance/multi-variant endpoints (including traffic shifting, shadow testing, and A/B deployments) and Bedrock inference profiles (Priority/Flex tiers, cross-Region routing for throughput and cost balancing).
• Hands-on work with EC2 Auto Scaling in ML contexts, including handling GPU instance availability constraints, spot interruption recovery, and cost-effective scaling for bursty inference workloads.
• Familiarity with advanced deployment patterns such as blue/green deployments, canary rollouts, and rollback automation to minimize production impact during model updates.

If you are a pragmatic, AWS-savvy engineer excited about operationalizing cutting-edge ML in mission-critical industries, this role offers the opportunity to build resilient systems that directly impact our company's innovation and customer outcomes. Join a dynamic team committed to excellence, with ample room for growth and technical leadership.

We are hiring an experienced Solutions Engineer to support Silicon Photonics (SiPh) test solutions for semiconductor customers, including foundries, IDMs, and OSATs.

This role combines pre‑sales technical support with post‑sales customer account technical support, working closely with customer test and engineering teams to ensure successful solution adoption, ramp‑up, and ongoing operation in R&D, NPI, and manufacturing environments.

Key Responsibilities

Post‑Sales Customer Account Technical Support (Primary Focus)

• Serve as the primary technical point of contact for assigned customer accounts after solution deployment.
• Provide ongoing post‑sales technical support to ensure successful installation, ramp‑up, optimization, and steady‑state operation of SiPh test solutions.
• Troubleshoot SiPh test‑related issues and coordinate closely with internal applications, service, and engineering teams for timely resolution.
• Maintain regular technical engagement with customer test and engineering teams to ensure system stability, customer satisfaction, and long‑term account support.
• Support customers through process changes, test enhancements, and new application requirements as they evolve.

Pre‑Sales Technical Support

• Provide technical support during customer engagements for SiPh test solutions.
• Understand customer test requirements and recommend appropriate test configurations, instruments, and measurement methodologies.
• Support customer technical discussions, evaluations, and demonstrations.
• Collaborate with sales teams to support technical alignment throughout the opportunity cycle.

Qualifications

• Bachelor’s or Master’s degree in Electrical Engineering, Photonics, Physics, Semiconductor Engineering, or a related field.
• 4–5+ years of experience in solutions engineering, applications engineering, test engineering, or related semiconductor roles.
• Hands‑on experience supporting SiPh or optical test solutions in R&D, NPI, or manufacturing environments.
• Solid understanding of optical and electrical testing concepts, test automation, and system‑level integration.
• Strong communication skills and ability to work independently in customer‑facing roles.

Added Advantage

• Experience or exposure to Wafer Acceptance Test (WAT) / parametric test solutions in semiconductor manufacturing or engineering environments.

We are seeking a skilled and experienced Product Security Engineer to design, develop, and integrate AI/ML‑enabled capabilities into Keysight’s security solutions as part of the Software Development Life Cycle (SDLC). This role is hands‑on and development‑focused, emphasizing software engineering excellence and applied AI/ML.

You will contribute to building intelligent features and automation that improve product security, quality, efficiency in developer workflows. Familiarity with secure software practices is considered a plus. The primary focus is on software development, AI/ML integration, and learning at scale.

About the Team:

You will collaborate with product owners, security researchers, and full stack engineers to build advanced autonomous security capabilities that enhance Keysight’s Software Development Life Cycle (SDLC).

Key Responsibilities:

Software Development

• Design, implement, test, and maintain backend services and tools using Python and related ecosystems.
• Build well‑structured, maintainable, and testable code following modern software engineering practices.
• Collaborate in design reviews, code reviews, and agile ceremonies to deliver high‑quality features.

Applied AI/ML

• Develop and integrate AI/ML models or services into production software systems.
• Work with structured and unstructured data to support training, validation, and inference pipelines.
• Integrate ML capabilities with APIs, services, and user interfaces.

Automation & SDLC Integration

• Contribute to automation that integrates with CI/CD pipelines and development workflows.
• Assist in building data ingestion, processing, and evaluation pipelines to support intelligent features.

Collaboration

• Work closely with software engineers, data practitioners, product owners, and quality engineers.
• Communicate technical designs and implementation details clearly across teams.

Must Haves:

• Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, AI/ML, or a related field.
• 3–5 years of hands‑on software development experience, with a preference for work involving AI/ML or data‑driven systems.
• Strong proficiency in Python with experience building and maintaining production‑grade software.
• Solid understanding of data structures, algorithms, and object‑oriented design.
• 1–3+ years of practical AI/ML exposure, such as:
• Developing, training, deploying, or integrating machine learning or agentic AI models
• Embedding AI/ML capabilities into production software systems
• Experience with Git, modern CI/CD pipelines, and standard development workflows.
• Familiarity with LLMs or AI‑assisted workflows is a plus.
• General awareness of secure software development practices is helpful but not required.
• Ability to work independently, contribute to technical decisions, and collaborate effectively across teams.
• Clear communication skills and proven ability to work in cross‑functional environments.

We Value:

• Master’s degree in Computer Science, Computer Engineering, Software Engineering, or a related technical field.
• Strong interest in software craftsmanship and applied AI/ML.
• Curiosity and willingness to learn new tools, frameworks, and technologies.
• Practical problem‑solving skills and attention to detail.
• Ability to work cross‑functionally and contribute positively to team outcomes.