Senior Machine Learning Engineer at Steampunk, Inc. in US-VA-McLean

Job description

• We are looking for a seasoned Senior Machine Learning Engineer to join our team of Data Architects and Developers, bridging the rigor of data science with the engineering discipline needed to build and ship production AI systems. This hybrid role spans the full ML lifecycle - from exploratory data analysis, feature engineering, and model experimentation through to building, integrating, and deploying scalable AI/ML and generative AI solutions. We are looking for more than a model builder: we need a technologist with strong software engineering fundamentals, excellent communication and customer service skills, and a passion for turning data and cutting-edge AI techniques into robust, mission-ready capabilities.

Responsibilities

• Develop end-to-end ML/AI solutions spanning predictive models, LLM-powered applications, multi-agent workflows, and RAG pipelines on structured and unstructured datasets.
• Perform exploratory data analysis, feature engineering, and data visualization to inform model design and validate assumptions.
• Apply deep learning methodologies and state-of-the-art libraries and frameworks to build and improve models.
• Integrate AI/ML models with enterprise systems, APIs, data platforms, vector databases, and cloud-native services to deliver scalable mission capabilities.
• Design and implement advanced prompt strategies, context management layers, retrieval systems, and LLM orchestration logic.
• Build scalable inference services, optimize model performance, and collaborate with MLOps/LLMOps to enable robust deployment, monitoring, and continuous improvement.
• Develop and execute comprehensive test plans for AI/ML models, including functional, regression, and edge case testing.
• Design test cases to evaluate performance, accuracy, bias, fairness, and robustness of AI outputs, and conduct adversarial and stress testing to assess model resilience.
• Track key quality metrics such as precision, recall, F1 score, false positives/negatives, and usability metrics; document and report 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 software development lifecycle, contributing reusable AI components, libraries, and APIs that accelerate delivery across programs.
• Collaborate with product managers, data architects, designers, and mission stakeholders to translate mission needs into intuitive, reliable AI-powered features.
• Mentor junior developers, conduct code reviews, and support engineering excellence across multi-disciplinary AI delivery teams.
• Stay current with emerging AI techniques, libraries, foundation models, and agent frameworks, evaluating their applicability to client missions.
• Contribute to the growth of our AI & Data Exploitation Practice.

Requirements

• Ability to obtain and maintain a U.S. government security clearance.
• Bachelor's, Master's, or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, or a related scientific/technical discipline.
• 7+ years of total experience.
• 3-5 years of industry experience developing ML/AI solutions, including hands-on experience with generative AI or LLM-driven application development.
• Demonstrated 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.
• Experience implementing 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 programming proficiency in SQL, R, Scala, or Java.
• Data visualization skills in Tableau, Power BI, D3, ArcGIS, or similar.
• Strong understanding of cloud platforms (AWS, Azure, GCP), including compute, serverless services, and security fundamentals for AI workloads, with tools such as AWS SageMaker or Azure HDInsight.
• Working knowledge of containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for AI-based systems.
• Experience with Git, Bash, and Unix commands, and familiarity with DevSecOps, MLOps, and LLMOps practices as applied to AI/ML delivery.
• Understanding of responsible AI principles including safety, fairness, privacy, bias mitigation, and model risk management.
• Strong analytical and communication skills with the ability to collaborate across engineering, design, and mission domains.
• Proven experience mentoring teammates and raising the technical bar of development teams.
• Familiarity with Flask, Solr, or Elasticsearch is a plus.

Skills

Required

• Python
• PyTorch
• TensorFlow
• Keras
• Hugging Face Transformers
• LangChain
• LlamaIndex
• RAG architectures
• embeddings
• vector stores
• context retrieval patterns
• multi-agent orchestration

Preferred

• Flask
• Solr
• Elasticsearch