Remote Machine Learning Engineer

Description:

• This role is for one of the Weekday's clients.
• The position is full-time and requires a minimum of 4 years of experience.
• The Machine Learning Engineer will own ML data, training, and deployment pipelines end-to-end, making them faster, more reliable, and scalable for enterprise use.
• Responsibilities include designing the architecture, optimizing for performance and parallelism, and driving improvements in UX and MLOps across the ML lifecycle.
• Key responsibilities include optimizing ETL and storage workflows to handle very large datasets (up to ~25M time series), managing ingestion, feature engineering, training, evaluation, deployment, and monitoring, building distributed compute solutions to enhance parallelism and reliability, developing CI/CD pipelines for models and data, and collaborating with design and product teams to simplify complex ML tasks within a no-/low-code environment.

Requirements:

• Candidates must have 3–6 years of product development experience in data- or ML-focused systems.
• Strong computer science and software engineering fundamentals are required.
• Expertise in data engineering and ETL pipelines is necessary.
• Experience with dataset integration and lifecycle orchestration with SQL/NoSQL stores is required.
• Proficiency in CI/CD pipelines and MLOps tooling is essential.
• Candidates must be skilled in programming with Python, SQL, and REST API development.
• Nice-to-haves include experience with Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure), exposure to Ray or other distributed-compute frameworks, and familiarity with model monitoring, experiment tracking, and data lineage.
• Traits for success include a high ownership and collaborative mindset, strong systems thinking, comfort with ambiguity, clear communication skills in cross-functional settings, and a product-driven approach that values user experience.

Benefits:

• The job offers the opportunity to work on cutting-edge ML technologies and contribute to significant improvements in enterprise ML pipelines.
• Employees will have the chance to collaborate with design and product teams, enhancing their skills in a cross-functional environment.
• The role provides a platform for professional growth in the fields of machine learning, data engineering, and MLOps.
• The position encourages a culture of ownership and innovation, allowing engineers to make impactful contributions to the company's success.