Overview In this role you will design and deploy scalable ML solutions for enterprise clients, partnering with data scientists, engineers, and client teams. You'll translate business needs into data-driven models and production-ready pipelines, working across cloud platforms to deliver measurable impact. You'll lead and mentor junior engineers while growing CapTech's ML and Data Science practice through client engagements and new proposals. This is a hands-on, cross-functional role at the intersection of technology and business outcomes, with a focus on producing scalable, high-value ML systems.
Compensation / Benefits- flexible work environment
- comprehensive benefits package
- generous PTO
- health coverage
- 401(k) matching
- Learning & Development programs
Responsibilities- Strategize with cross-functional teams to implement end-to-end ML solutions and explore new approaches
- Provide technical leadership and ensure alignment of solutions with customer needs
- Deconstruct client needs into data-driven processes and analytical measures
- Analyze and transform large datasets across enterprise data platforms (AWS, Azure, GCP)
- Design, develop, and deploy advanced analytical solutions (e.g., recommender systems, NLP, risk scoring)
- Productionize ML systems focusing on optimization and scalability
- Grow ML/Data Science practices through client presentations, proposals, and leading teams of junior data scientists and engineers
Key requirements- 7+ years of experience delivering data engineering and ML solutions on cloud platforms
- Bachelor's degree or equivalent combination of education and experience
- Experience providing technical leadership and mentoring in data engineering
- Hands-on experience with large-scale data (multi-billion records)
- Proficiency in Python, Scala, or similar languages
- Strong SQL, Spark, NoSQL, and cloud data processing in production
- Docker and microservices experience
- Data warehousing experience with Snowflake, Databricks, Azure SQL, or Amazon RDS
- Experience deploying production-scale ML systems across domains (personalization, NLP, CV)
- Knowledge of DevOps, automation, statistics, model management/versioning
- Experience with LLMs in production and related techniques (prompt engineering, MCP, RAG, agentic AI)
- Familiarity with Langchain, n8n, pydantic, and multi-agent orchestration
- Collaborative mindset
- Strong communication and client-facing presence
- Mentorship and team leadership
- Python
- Scala
- SQL
