Senior Applied AI-Machine Learning Engineer

Atlas Technologies•North Charleston, SC

About The Position

Atlas Tech is seeking a Senior Applied AI/ML Engineer to design, build, and operationalize advanced AI/ML solutions for mission, operational, and business problems. The role combines hands-on engineering with technical leadership, including developing AI-enabled applications, deploying them into production, shaping solution architectures, selecting models and frameworks, running experiments, and delivering reliable capabilities with measurable value. The engineer will work closely with product, engineering, and domain teams, and should be comfortable across research, prototyping, and applied engineering.

Requirements

Bachelor’s or master’s degree in Computer Science, Machine Learning, Data Science, Engineering, or a related field.
At least 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 foundation-model fine-tuning, including training, evaluation, and integration into production pipelines.
Strong proficiency in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn, Hugging Face, or LangChain, or similar tools.
Experience building and operating AI/ML systems in air-gapped environments.
Deep understanding of model development, including supervised and unsupervised learning, neural networks, transformers, time series, and embeddings.
Familiarity with modern AI/ML operations tools such as 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.
Curiosity, experimentation, practical judgment, and the ability to turn loosely defined problems into working solutions.

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.

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 by defining hypotheses, running evaluations, assessing model performance, and identifying improvement strategies.
Collaborate with engineering teams to build robust, secure, and maintainable AI-enabled architectures.
Provide periodic instruction and prompt fine-tuning to address newly discovered hallucination vectors, user-reported biases, or changes in operational terminology.
Partner with domain subject-matter experts 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, including bias evaluation, data governance, model explainability, and ethical use of automated systems.
Prepare demos, prototypes, and proof-of-concept integrations that illustrate feasibility and value.
Present concepts and prototypes and explain technical tradeoffs.