CapTech is an award-winning consulting firm that collaborates with clients to achieve what’s possible through the power of technology. The Lead Machine Learning / Data Science Engineer will be responsible for designing and implementing data-driven solutions for clients, with a focus on building and deploying scalable machine learning systems in enterprise environments.
Requirements
- Strategize with clients, data scientists, engineers, and other members of cross-functional teams to implement end-to-end machine learning solutions and identify new machine learning and data science approaches to meet business needs
- Provide technical leadership and collaborate within and across teams to ensure that the overall technical solution is aligned with the customer needs
- Deconstruct client needs into data-driven processes/models and analytical measures
- Analyze and transform large datasets hosted on a variety of enterprise-level data platforms
- Design, develop, and deploy advanced analytical solutions leveraging client data
- Productionize ML systems with a focus on optimization and scalability to satisfy clients’ requirements
- Grow CapTech’s Machine Learning and Data Science practices through delivering client presentations, writing proposals, attending various business development events, and leading teams of junior data scientists and engineers
- Experience providing technical leadership and mentoring other engineers in data engineering space
- Hands-on experience manipulating and analyzing large (multi-billion record) data sets
- Hands-on experience developing data-driven solutions using Python, Scala, or similar languages
- Proficiency leveraging SQL, Spark, NoSQL, and/or cloud data processing frameworks in a production setting
- Proficiency with containerization (e.g., Docker) and microservices
- Proficiency with data warehousing tools/environments such as Snowflake, Databricks, Azure SQL, Amazon RDS
- Experience applying analytical methods across multiple business domains
- Hands-on experience implementing production-scale machine learning systems in one or more domains
- Knowledge of DevOps and automation best practices
- Knowledge of statistics and statistical modeling methods
- Knowledge of model management and model versioning best practices
- Experience working with LLMs (e.g., GPT, Claude, Mistral, etc.) in production setting
- Experience with prompt engineering, MCP and RAG, and agentic AI architectures
- Strong understanding of conversational UX and prompt evaluation metrics
- Experience with agentic frameworks in practice (langchain, n8n, pydantic, etc.)
- Experience with multi-agent orchestration
Benefits
- Generous Paid Time Off
- Health coverage
- Disability insurance
- Paid family leave
- 401(k) Matching
- Employee Resource Groups
- Philanthropic Partnerships
- Learning & Development – Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths
- Modern Health –A mental health and well-being platform that provides 1:1 care, group support sessions, and self-serve resources to support employees and their families through life’s ups and downs
- Carrot Fertility –Inclusive fertility and family-forming coverage for all paths to parenthood – including adoption, surrogacy, fertility treatments, pregnancy, and more – and opportunities for employer-sponsored funds to help pay for care
- Fringe –A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them – ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more
