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CapTech Consulting

Consulting firm delivering data-driven business growth

Lead Machine Learning / Data Science Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeAtlanta, GA, USA

About the Job

Requirements

  • At least 7 years of experience delivering data engineering and machine learning solutions on cloud platforms.
  • A bachelor's degree or an equivalent combination of education and experience.
  • Experience providing technical leadership and mentoring other engineers in data engineering.
  • Hands-on experience manipulating and analyzing large datasets, including multi-billion-record datasets.
  • 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, such as Docker, and microservices.
  • Proficiency with data warehousing tools or environments such as Snowflake, Databricks, Azure SQL, and Amazon RDS.
  • Ability to frame data-driven problems from cross-industry business requirements.
  • Experience applying analytical methods across multiple business domains, such as customer analytics, marketing, finance, and digital channels.
  • Hands-on experience implementing production-scale machine learning systems in one or more domains, such as personalization, natural language processing, or 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 large language models such as GPT, Claude, or Mistral in a production setting.
  • Experience with prompt engineering, MCP, RAG, and agentic AI architectures.
  • Understanding of conversational user experience and prompt evaluation metrics.
  • Experience with agentic frameworks in practice, such as LangChain, n8n, or Pydantic.
  • Experience with multi-agent orchestration.

Responsibilities

  • Strategize with clients, data scientists, engineers, and other cross-functional team members to implement end-to-end machine learning solutions and identify machine learning and data science approaches that meet business needs.
  • Provide technical leadership and collaborate within and across teams to align the overall technical solution with customer needs.
  • Deconstruct client needs into data-driven processes, models, and analytical measures.
  • Analyze and transform large datasets hosted on enterprise-level data platforms such as AWS, Azure, and GCP.
  • Design, develop, and deploy advanced analytical solutions leveraging client data, such as recommender systems, natural language processing, and risk scoring.
  • Productionize machine learning systems with a focus on optimization and scalability to satisfy client requirements.
  • Grow the Machine Learning and Data Science practices by delivering client presentations, writing proposals, attending business development events, and leading teams of junior data scientists and engineers.

About the Company

CapTech Consulting

Consulting firm delivering data-driven business growth

CapTech is a national consulting firm that helps organizations grow efficient, successful businesses by bringing data, systems, and ingenuity into design and execution. It blends technical depth, analytical skill, and creative problem solving to build customized solutions across industries, turning ideas into action and moving business forward. CapTech differentiates itself through its people-focused culture—empowering consultants to bring their whole selves, fostering growth with innovative technologies, and supporting healthy work-life integration—along with a hands-on, problem-solving approach that combines depth in tech with practical, actionable outcomes. The company’s goal is to enable clients to use technology, management, and insight to deliver results that exceed expectations, which is reflected in its decade-plus presence on the Inc. 5000 list.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Richmond, VA
Founded
1997

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