Senior Applied AI-Machine Learning Engineer

Atlas Technologies•North Charleston, SC

About The Position

We are seeking a Senior Applied AI/ML Engineer to design, build, and operationalize advanced AI/ML solutions that solve high-impact mission, operational, and business problems. This role blends deep technical expertise with practical, hands-on engineering, building AI enabled applications, deploying them into production systems, and working closely with product, engineering, and domain teams to deliver measurable value. You will play a lead role in shaping solution architectures, selecting the right models and frameworks, developing experiments, and translating complex concepts into working capabilities that end users can rely on. The ideal candidate is equally comfortable in research, prototyping, and applied engineering environments.

Requirements

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

Nice To Haves

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)

Responsibilities

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