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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Machine Learning / Data Science Engineer - **Company:** CapTech Consulting - **Location:** Richmond, VA, United States (Remote available) - **Experience:** Expert - **Salary:** $90,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Computer Vision, Microsoft Azure, Big Data, Cloud Database, Information Engineering, Data Files, Data Warehousing, DevOps, Python (Programming Language), Machine Learning, SQL Azure, Natural Language Processing, NoSQL, Recommender Systems, SQL Databases, Google Cloud, Large Language Models, Snowflake, Prompt Engineering, Apache Spark, Amazon Relational Database Service, Containerization, Data Analytics, Nintex, Data Management, Machine Learning Operations, GPT, Software Version Control, Docker, Databricks, Microservices - **Published:** June 30, 2026 - **Apply:** https://jobs.smartrecruiters.com/CapTechConsulting/744000135096698-lead-machine-learning-data-science-engineer- ## About the Role * 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, 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. ## 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., * 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. ## Related Videos - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [Speak, Code, Deploy: Transforming Developer Experience with Voice Commands](https://www.wearedevelopers.com/videos/1159-speak-code-deploy-transforming-developer-experience-with-voice-commands) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [The Prompt Engineer ✍️](https://www.wearedevelopers.com/magazine/216-the-prompt-engineer) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Prompt Engineering is a Job of the Past](https://www.wearedevelopers.com/magazine/342-prompt-engineering-is-a-job-of-the-past) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)