Senior Machine Learning Engineer
Responsibilities
- Design and build end-to-end ML pipelines covering feature engineering, model training, backtesting, validation, reporting, and batch inference.
- Convert data science prototypes into reliable and maintainable production solutions.
- Develop a configurable ML framework using reusable components and parameter-driven workflows.
- Build and maintain Python-based ML workflows using an existing codebase.
- Support data preparation and transformation workflows in Snowflake and dbt Cloud.
- Implement data quality checks, automated testing, versioning, monitoring, and CI/CD.
- Integrate model outputs into downstream business systems and operational workflows.
- Contribute to architecture decisions and propose practical implementation approaches.
- Support production operations, troubleshooting, model refreshes, and continuous improvement.
- Collaborate with data scientists, data engineers, architects, and business stakeholders.
Requirements
- 6–8 years of experience in machine learning engineering, software engineering, data engineering, or a related field.
- Strong Python software engineering skills, including experience with reusable and object-oriented code.
- Experience building production ML pipelines.
- Hands-on experience with traditional ML methods and libs (pandas, NumPy, scikit-learn, PyTorch).
- Hands-on experience with Docker.
- Strong SQL and data engineering skills.
- Practical experience with Snowflake and dbt Cloud.
- Experience working with AWS.
- Experience with Git-based CI/CD workflows, such as GitHub Actions.
- Understanding of testing, monitoring, versioning, reproducibility, and production support.
- Strong communication, ownership, troubleshooting, and problem-solving skills.
Nice to have
- Experience with scheduled batch prediction pipelines.
- Experience building configurable frameworks that support multiple products or business units.
- Familiarity with CRM or other downstream business-system integrations.
- Familiarity with Kubernetes, workflow orchestration, or infrastructure as code.
- Exposure to generative AI or LLM-based applications.
- Experience in pharmaceutical, biotechnology, healthcare, or life sciences environments.
We offer
- Competitive compensation
- Flexible working hours
- Continuous education, mentoring, and professional development programs
- A team with an excellent tech expertise
- Contract through the end of the year, with a possible extension based on project needs and performance.
