Data & ML Engineer

About the role

Foster Weise Covey is hiring a Data & ML Engineer to build intelligent, production-grade data systems that turn experiments into business impact. This is not a dashboarding role: you will own the full lifecycle, from pipeline architecture and ETL automation to model training, deployment and drift monitoring in production.

Key responsibilities

• Design and maintain scalable data architectures that feed ML models and analytical workflows
• Build, validate and deploy supervised, unsupervised and recommender models into production
• Automate ETL/ELT pipelines with quality, reliability and observability
• Implement MLOps: versioning, CI/CD for models, and monitoring for data and model drift
• Work with AI Product Engineers to integrate models into APIs and services
• Run cross-validation, A/B testing and hyperparameter tuning aligned to business KPIs
• Document models, metrics and pipelines with the traceability required in production

Required profile

• 2-3 years of hands-on experience in data engineering and ML
• Degree in Data Engineering, Computer Science, AI or a related field
• English at intermediate level or above
• Curious, proactive, methodical, comfortable tackling complex problems independently and working well in a team

Required skills

• Advanced Python and SQL (SQL Server, stored procedures, functions and jobs)
• AWS: Redshift, Athena, S3, Lambda, Step Functions, SNS/SQS, Personalize
• TensorFlow (advanced) and PyTorch (intermediate)
• MLOps: Git, CI/CD, production model lifecycle management
• ETL processes, statistical modeling, regression and classification
• LLMs and embeddings, NoSQL, REST APIs and C#/.NET are a plus

What we offer

• A technical environment where work ships to production and has measurable business impact
• Collaboration with cross-functional teams across business units
• A clear path to grow alongside a product and data team that takes craft seriously