Lead Applied AI/ML Engineer: Build Real-World AI Solutions

Atlas Tech; Nashville (TN); On-site; USD 140,000 - 190,000; Full time

Job summary

Atlas Tech is seeking a Senior Applied AI/ML Engineer to design, build, and operationalize advanced AI/ML solutions that address mission, operational, and business challenges. You will lead architecture, model selection, and end-to-end pipelines, delivering production-ready AI capabilities across APIs, microservices, and secure environments.

The role requires hands-on coding, experimentation, and collaboration with product and domain teams to translate requirements into tangible value.

Qualifications

• 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

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.

Skills

Python

TensorFlow

PyTorch

scikit-learn

Hugging Face

LangChain

LLMs / fine-tuning

RAG

vector databases

embeddings

LoRA adapters

production deployments

APIs / microservices

CI/CD for ML

communication with executives

Education

Bachelor’s or Master’s degree in Computer Science, ML, Data Science, Engineering, or related field

Tools

MLflow

SageMaker

Vertex AI

Databricks

Job description

Atlas Tech is seeking a Senior Applied AI/ML Engineer to design, build, and operationalize advanced AI/ML solutions that address mission, operational, and business challenges. You will lead architecture, model selection, and end-to-end pipelines, delivering production-ready AI capabilities across APIs, microservices, and secure environments.

The role requires hands-on coding, experimentation, and collaboration with product and domain teams to translate requirements into tangible value.