Senior Applied AI-Machine Learning Engineer

• Design, build, and deploy scalable AI/ML tools for generative AI use cases
• Develop end-to-end ML pipelines, including LLM tool integration, data ingestion, feature engineering, model training, evaluation, and monitoring
• Implement production-grade inference systems and integrate ML models into applications, APIs, and microservices
• Lead experimentation, define hypotheses, run evaluations, assess model performance, and identify improvement strategies
• Work closely with engineering teams to build robust, secure, and maintainable AI-enabled architectures
• Provide periodic instruction and prompt fine-tuning to resolve newly discovered hallucination vectors, user-reported biases, or changes in operational terminology.
• Partner with domain SMEs to translate real-world constraints into effective features, labels, and model requirements
• Evaluate emerging AI technologies, frameworks, and foundation models and recommend their use in mission-relevant applications
• Mentor junior engineers and contribute to internal standards, coding practices, and reusable components
• Ensure responsible AI practices, bias evaluation, data governance, model explainability, and ethical use of automated systems
• Prepare demos, prototypes, and proof-of-concept integrations that clearly illustrate feasibility and value

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, Engineering, or related field
• 3+ years of experience in applied AI/ML engineering, including production deployments
• Experience with LLMs, fine-tuning, retrieval-augmented generation (RAG), prompt engineering, or custom model training
• Experience with vector databases, high-dimensional embeddings, and semantic search
• Experience applying LoRA adapters for efficient fine-tuning of foundation models, including training, evaluation, and integration into production pipelines
• Strong proficiency in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn, Hugging Face, LangChain, or similar
• Experience building and operating AI/ML systems in air-gapped environments
• Deep understanding of model development: supervised/unsupervised learning, neural networks, transformers, time-series, embeddings
• Familiarity with modern AI/ML ops tooling: MLflow, SageMaker, Vertex AI, Databricks, or equivalent
• Strong understanding of API design, microservices, containers, and CI/CD for ML
• Ability to connect technical solutions to business value and communicate effectively with executives and non-technical stakeholders, * Experience with Azure AI Foundry environments
• Exposure to reinforcement learning or agentic systems
• Experience building real-time or low-latency ML inference systems
• Experience in mission-driven, regulated, or national security-oriented environments (if applicable)
• Strong UI/UX or front-end awareness for integrated model experiences (optional), A senior engineer who is:
• Curious and experimental, but also practical and grounded
• Capable of taking a loosely defined problem and creating a working solution
• Comfortable presenting concepts, demoing prototypes, and explaining tradeoffs
• Passionate about building AI systems that deliver measurable, real-world impact

Atlas Tech offers a competitive salary, generous benefits package, and an opportunity to make a positive impact in your own community.

“From day 1, I knew Atlas Tech was where I wanted to be. Atlas’ culture embraces creativeness, community involvement, and taking care of their employees. If you’re looking for a great place to work, come join us!” - Blane