Senior ML Engineer

Alterdata.io is a data services company seeking a contractor for the role of Senior ML Engineer. The company works on implementing machine learning (ML) and artificial intelligence (AI) systems, focusing on building scalable ML infrastructure and platforms primarily using GCP / Vertex AI, Python, Docker, and SQL.

• Commercial experience as an ML Engineer or similar role focused on AI deployment.
• Proficient knowledge of Python and SQL.
• Hands-on experience with ML/DL libraries and frameworks such as PyTorch, TensorFlow, scikit-learn, XGBoost.
• Practical experience designing and implementing the full ML model lifecycle.
• Experience working with large language models.
• Familiarity with experiment tracking and model/data versioning tools like MLflow, Weights & Biases, DVC, Feast/Feature Store.
• Experience building efficient model APIs for batch and online prediction.
• Practical experience working with cloud platforms and proficiency in Docker and serverless technologies.
• Knowledge of MLOps tools in cloud environments such as GCP Vertex AI and AWS SageMaker.
• Familiarity with CI/CD practices adapted to ML projects (automatic testing, retraining, deployment pipelines) using tools like GitHub Actions, GitLab CI.
• Self-motivated, proactive, and capable of solving complex technical problems.
• Good work organization, teamwork, and effective communication skills.
• English language proficiency at minimum C1 level.
• Ability to interpret business goals and translate them into coherent technological tasks considering the technical context.
• Experience using AI tools in coding workflows, such as Cursor or Claude Code.

Nice to have:

• Experience with Terraform or other Infrastructure as Code tools.
• Knowledge of ML workflow orchestration tools.
• Experience with distributed data processing technologies such as BigQuery, Snowflake, PySpark.
• Experience with tools like DBT, Dataform.
• Familiarity with data integration, storage, processing, and search tools in environments like Google DataFlow, Snowpark, AWS Data Migration Services, Azure DataFactory.
• Experience as a technical team lead or coordinator of small development teams.

• Design and develop highly scalable and secure ML and MLOps infrastructure based on cloud platforms, particularly GCP / Vertex AI.
• Deploy ML and GenAI models to production and create fast, secure APIs for model serving.
• Oversee stability, automation, and performance of full ML pipelines from data collection, training, evaluation to continuous deployment (CT/CD).
• Monitor model quality in production and optimize computational resource performance and costs (GPU/CPU, FinOps).
• Write clean, modular, maintainable code in Python and SQL adhering to best testability, safety, and MLOps/CI-CD practices.
• Design and standardize generic data integration mechanisms from diverse sources such as APIs, real-time streams, and databases.
• Collaborate with Architects, Data Scientists, and business teams to translate business goals into optimal AI system architecture and KPIs (ROI, model evaluation metrics).
• Maintain ML technical quality by performing code reviews, mentoring less experienced contractors, and promoting ML engineering and MLOps standards.
• Lead architectural documentation and actively contribute to agile delivery process improvements.

Position is offered as a B2B contract for fully remote cooperation. The contractor is expected to provide services using their own computer equipment and basic tools; project licenses are provided by the client. Guaranteed order volume of approximately 140-180 hours per month.