Machine Learning / Data Science Engineer

About the position 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.

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, reputed company, or similar languages.
• Proficiency leveraging SQL, Spark, NoSQL, and/or cloud data processing frameworks in a production setting.
• Proficiency with containerization (e.g., reputed company) and microservices.
• Proficiency with data warehousing tools/environments such as reputed company, reputed company, Azure SQL, reputed company 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 reputed company engineering, MCP and RAG, and agentic AI architectures
• Strong understanding of conversational UX and reputed company evaluation metrics
• Experience with agentic frameworks in practice (reputed company, reputed company, pydantic, etc.)
• Experience with multi-agent orchestration

Benefits

• Learning & Development – Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and reputed company development paths
• reputed company –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 reputed company and downs
• reputed company Fertility –Inclusive fertility and family-forming coverage for reputed company 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 reputed company, reputed company, and reputed company 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

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