Machine Learning / Data Science Engineer
CapTech · Chicago, IL · 1 mo ago
On-siteConsulting$90k/yrFull-time
About the role
CapTech Machine Learning Engineers are responsible for designing and implementing data-driven solutions for our clients, with a specific focus on building and deploying scalable machine learning systems in enterprise environments. CapTech employees enjoy a collaborative environment and have many opportunities to learn from and share knowledge with other CapTech analysts, architects, and our clients.
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
- 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
- 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)
- Experience working with LLMs (e.g., GPT, Claude, Mistral, etc.) in production settings
- 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
Requirements
- Bachelor's degree or equivalent combination of education and experience
- 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
- Knowledge of DevOps and automation best practices
- Knowledge of statistics and statistical modeling methods
- Knowledge of model management and model versioning best practices
Benefits
- Generous PTO, health coverage, disability insurance, and paid family leave
- Extended benefits including:
- 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 providing 1:1 care, group support sessions, and self-serve resources
- Carrot Fertility – Inclusive fertility and family-forming coverage for all paths to parenthood, including employer-sponsored funds
- Fringe – A company-paid stipend program for personalized lifestyle benefits (e.g., Netflix, Spotify, GrubHub, student loan repayment, travel, fitness)
- Employee Resource Groups – Employee-led committees embracing diversity and inclusion
- Philanthropic Partnerships – Opportunities to engage in community support projects
- 401(k) Matching – Generous matching with no vesting period
Pay
The base pay range for this role is $90,000 - $200,000.
Schedule
CapTech is committed to providing a flexible work environment. Employees must be available to work onsite in a client location or a CapTech office as requested. Remote work is allowed when compatible with CapTech and client needs.