Lead Machine Learning / Data Science Engineer

About the role

CapTech is an award-winning consulting firm that collaborates with clients to achieve what’s possible through the power of technology. At CapTech, we’re passionate about the work we do and the results we achieve for our clients. From the outset, our founders shared a collective passion to create a consultancy centered on strong relationships that would stand the time. Today we work alongside clients that include Fortune 100 companies, mid-sized enterprises, and government agencies, a list that spans across the country.

Responsibilities

• Strategizing 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
• Deconstructing client needs into data-driven processes/models and analytical measures
• Analyzing and transforming large datasets hosted on a variety of enterprise-level data platforms (e.g., AWS, Azure, GCP)
• Designing, developing, and deploying advanced analytical solutions leveraging client data (e.g., recommender systems, natural language processing, risk scoring)
• Productionizing ML systems with a focus on optimization and scalability to satisfy clients’ requirements
• Growing 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

Qualifications

• 7+ years of experience delivering data engineering and machine learning solutions on cloud platforms
• Bachelor's degree or equivalent combination of education and experience
• 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
• Comfort and proficiency in framing data-driven problems from cross-industry business requirements
• Experience applying analytical methods across multiple business domains (e.g., customer analytics, marketing, finance, digital channels)
• Hands-on experience implementing production-scale machine learning systems in one or more domains (i.e., personalization, natural language processing, computer vision)
• 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

We want everyone at CapTech to be able to envision a lasting and rewarding career here, which is why we offer a variety of career paths based on your skills and passions. You decide where and how you want to develop, and we help get you there with customizable career progression and a comprehensive benefits package to support you along the way. Alongside our suite of traditional benefits encompassing generous PTO, health coverage, disability insurance, paid family leave and more, we’ve launched extended benefits to help meet our employees’ needs.

Pay

The base pay range for this role is: $90,000 - $200,000.

Schedule

CapTech is committed to providing a flexible work environment and helping our employees achieve a work-life balance that suits their individual needs. Employees must be available to work onsite in a client location or a CapTech office as requested. We allow CapTech employees to work remotely when compatible with CapTech and client needs.