Senior Machine Learning Engineer

Steampunk builds and ships production AI systems end-to-end, from early experimentation to reliable deployment. In this hybrid role in McLean, VA, you will help deliver mission-ready capabilities across predictive modeling, LLM-powered applications, multi-agent workflows, and RAG pipelines. You will work with a team that bridges data science rigor and engineering discipline, applying responsible AI practices while integrating scalable AI into enterprise environments.

Compensation & Work Setup

Salary range: USD 140,000 - 190,000 per year. Steampunk notes that compensation factors may include geographic location, contractual requirements, education, knowledge, skills, competencies, and experience.

This position is hybrid and located in McLean, VA.

What You’ll Do

• Develop end-to-end ML/AI solutions covering predictive models, LLM-powered applications, multi-agent workflows, and RAG pipelines using structured and unstructured datasets.
• Conduct exploratory data analysis, feature engineering, and data visualization to guide model design and validate assumptions.
• Use deep learning methodologies and modern libraries/frameworks to build, improve, and scale models.
• Integrate AI/ML solutions with enterprise systems, APIs, data platforms, vector databases, and cloud-native services to deliver scalable mission capabilities.
• Design prompt and retrieval capabilities, including prompt strategies, context management, retrieval systems, and LLM orchestration logic.
• Build and optimize inference services, partnering with MLOps/LLMOps to support deployment, monitoring, and continuous improvement.
• Create and execute comprehensive test plans, including functional, regression, and edge case testing for AI/ML models.
• Design evaluation approaches for performance, accuracy, bias, fairness, and robustness, including adversarial and stress testing.
• Track and report quality metrics such as precision, recall, F1 score, false positives/false negatives, and usability metrics, documenting defects and unexpected behaviors.
• Validate compliance with data privacy, security, and ethical AI standards, including safety guardrails, input sanitization, and content filtering.
• Support an Agile development lifecycle by delivering reusable AI components, libraries, and APIs that accelerate program execution.
• Collaborate with product managers, data architects, designers, and mission stakeholders to translate mission needs into reliable AI-powered features.
• Mentor junior developers, perform code reviews, and contribute to engineering excellence across multi-disciplinary AI teams.
• Stay current on emerging AI techniques, foundation models, and agent frameworks, evaluating applicability to client missions.
• Contribute to the growth of the AI & Data Exploitation Practice.

What You Bring

• U.S. government security clearance: ability to obtain and maintain.
• Education: Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, or a related technical discipline.
• 7+ years of total experience.
• 3-5 years of industry experience developing ML/AI solutions, including hands-on generative AI or LLM-driven application development.
• Experience manipulating structured and unstructured data for analysis, including data modeling and data solution development.
• Strong programming skills in Python and modern AI frameworks such as PyTorch, TensorFlow, Keras, Hugging Face Transformers, LangChain, or LlamaIndex.
• Proven experience with RAG architectures, embeddings, vector stores, and context retrieval patterns, plus familiarity with multi-agent orchestration and prompt engineering.
• Demonstrated experience in big data systems including Hadoop and Spark, and additional proficiency in SQL, R, Scala, or Java.
• Data visualization skills using Tableau, Power BI, D3, ArcGIS, or similar.
• Working understanding of cloud platforms (AWS, Azure, GCP) including compute, serverless services, and security fundamentals for AI workloads (example tools include AWS SageMaker and Azure HDInsight).
• Working knowledge of Docker, Kubernetes, and CI/CD pipelines for AI-based systems.
• Experience with Git, Bash, and Unix commands, with familiarity with DevSecOps, MLOps, and LLMOps.
• Knowledge of responsible AI principles including safety, fairness, privacy, bias mitigation, and model risk management.
• Strong analytical and communication skills, including collaboration across engineering, design, and mission domains.
• Proven experience mentoring teammates and raising the technical bar of development teams.
• Plus: familiarity with Flask, Solr, or Elasticsearch.

Additional Notes

• Steampunk conducts interviews and assessments that require candidates to be on camera. Steampunk also reserves the right to take a picture to verify identity and prevent fraud.
• Steampunk is an equal opportunity employer.
• Steampunk participates in the E-Verify program.

Technologies you may work with: Python, PyTorch, TensorFlow, Keras, Hugging Face Transformers, LangChain, LlamaIndex, RAG architectures, embeddings, vector stores, Hadoop, Spark, SQL, R, Scala, Java, Tableau, Power BI, D3, ArcGIS, AWS, Azure, GCP, AWS SageMaker, Azure HDInsight, Docker, Kubernetes, CI/CD pipelines, Git, Bash, Unix commands, DevSecOps, MLOps, LLMOps, Flask, Solr, Elasticsearch, vector databases, APIs, data platforms, cloud-native services.