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The Machine Learning Engineer is responsible for the end-to-end development, deployment, and maintenance of machine learning (ML) and artificial intelligence (AI) solutions. This role requires a strong blend of data science, software engineering, and MLOps expertise to build robust, scalable, and secure AI/ML systems that address complex business challenges.

Responsibilities:

• Apply established machine learning and AI techniques to new problems and datasets.

• Build, optimize, and maintain machine learning and AI models and supporting pipelines.

• Evaluate and monitor ML/AI system outcomes, model performance, and data quality; define appropriate metrics and acceptance criteria.

• Identify issues in models, pipelines, and datasets; recommend and implement improvements.

• Design, develop, test, document, refactor, and maintain moderately complex programs/scripts to support ML development and deployment.

• Follow agreed engineering standards, tools, and best practices to deliver secure, reliable, and maintainable solutions.

• Monitor progress, report status, and communicate risks, blockers, and dependencies in a timely manner.

• Collaborate with teammates through code reviews, design reviews, and shared ownership of deliverables.

• Elicit requirements for ML/AI lifecycle practices, working methods, and automation (e.g., CI/CD, testing, deployment, monitoring).

• Select and implement appropriate lifecycle practices for components and microservices within the ML/AI solution.

• Deploy automation to support well-engineered, repeatable, and secure build/release processes.

• Define ML/AI modules needed for integration builds and produce buIld definitions for each release/generation of the solution.

• Validate and accept completed ML/AI modules against agreed functional, quality, and performance criteria.

• Apply data science techniques to new problems and datasets, using specialized programming approaches where needed.

• Identify and implement opportunities to improve training data, features, and model performance.

• Build and maintain data pipelines using data engineering standards and tools (ETL/ELT).

• Support monitoring of emerging technologies and contribute to internal reports, technology roadmaps, and knowledge sharing.

Essential Qualifications & Experience:

• 5+ years of hands-on experience building ML/AI solutions in Python, with strong foundations in machine learning concepts, software engineering, and production-grade development practices.

• Proven experience designing, developing, optimizing, and maintaining end-to-end AI/ML pipelines (data processing, training, evaluation, deployment, and monitoring).

• Strong track record in model evaluation and performance measurement, including defining metrics, running assessments, and monitoring model qualitY over time.

• Experience applying and adapting pre-trained models (including Generative AI/LLMs) to solve specific business use cases.

• Solid experience with MLOps practices: version control, experiment tracking, model packaging, deployment, monitoring, and automation.

• Proficiency with CI/CD pipelines and DevOps best practices (e.g., Git-based workflows, build/release automation).

• Practical experience with containerization (Docker, Podman) and orchestration using Kubernetes, including infrastructure provisioning and operationalization in cloud environments.

• Experience with workflow orchestration tools such as Apache Airflow and/or Argo Workflows.

• Strong experience building and maintaining REST APIs, ideally for serving ML models and AI services.

• Experience working with SQL and NoSQL databases.

Nice to have

• Experience building production-grade AI agent backends, e.g., using LangChain or pydantic-ai, wrapped in FastAPI services.

• Full-stack experience with TypeScript frameworks such as Next.js.

• Experience working in air-gapped / restricted-network environments.

If you've read the description and feel this role is a great match, we'd love to hear from you! Click "Apply for this job" to be directed to a brief questionnaire. It should only take a few moments to complete, and we'll be in touch promptly if your experience aligns with our needs.