Senior AI/ML Engineer: Build Production-Ready GenAI Solutions

Atlas Technologies, Inc.; Michigan; On-site; USD 140,000 - 190,000; Full time

Job summary

Atlas Technologies, Inc. is seeking a Senior Applied AI/ML Engineer to design, build, and operationalize advanced AI/ML solutions that solve mission-critical problems. The role blends research, prototyping, and applied engineering, leading solution architectures, model selection, experiments, and real-world integration into products and services.

You will mentor engineers, work with domain experts, ensure responsible AI practices, and deliver demonstrations that illustrate measurable 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

LLMs

RAG

Prompt engineering

Vector databases

Embeddings

LoRA adapters

API design

CI/CD for ML

Docker/containers

MLflow

SageMaker

Vertex AI

Education

Bachelor’s or Master’s in CS/ML/DS/Engineering

Tools

MLflow

SageMaker

Vertex AI

Databricks

Docker

Kubernetes

Job description

Atlas Technologies, Inc. is seeking a Senior Applied AI/ML Engineer to design, build, and operationalize advanced AI/ML solutions that solve mission-critical problems. The role blends research, prototyping, and applied engineering, leading solution architectures, model selection, experiments, and real-world integration into products and services.

You will mentor engineers, work with domain experts, ensure responsible AI practices, and deliver demonstrations that illustrate measurable value.