Machine Learning / Data Science Engineer

Job Description

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.

Specific responsibilities for the Machine Learning Engineer position include:

• 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.

Qualifications

• 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.
• 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

Additional Information

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.

• 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.
• 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
• Employee Resource Groups – Employee-led committees that embrace and incorporate diversity and inclusion into our day-to-day operations
• Philanthropic Partnerships – Opportunities to engage in partnerships and pro-bono projects that support our communities.
• 401(k) Matching – Generous matching and no vesting period to help you continue to build financial wellness

CapTech is an equal opportunity employer committed to fostering a culture of equality, inclusion and fairness — each foundational to our core values. We strive to create a diverse environment where each employee is encouraged to bring their unique ideas, backgrounds and experiences to the workplace. For more information about our Diversity, Inclusion and Belonging efforts, click HERE. As part of this commitment, CapTech will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Laura Massa directly via email lmassa@captechconsulting.com.

At this time, CapTech cannot transfer nor sponsor a work visa for this position. Applicants must be authorized to work directly for any employer in the United States without visa sponsorship.