Generative AI/ML Engineer – Onsite Client Solutions

Slalom; Atlanta (GA); On-site; USD 106,000 - 181,000; Full time

Benefits offered by this job

Health insurance

Dental coverage

Vision coverage

401(k) with match

Well-being reimbursement

Discounts on insurance

Job summary

Slalom is seeking a technologist to design, build, and deploy generative AI and ML solutions that address client business needs. You will develop LLM-powered applications with RAG, agents, and tool calling, and apply ML/DL to deliver practical AI tools. You’ll stay current with AI trends and contribute to mentoring and community growth.

You will bring 3+ years deploying models to production, plus 2-4 years in IT consulting, with strong communication and cloud fluency across AWS, GCP, or Azure.

Qualifications

• 3+ years implementing models into production.
• 2-4 years of professional consulting experience.
• Strong consultative and communication skills.
• Fluent in AI/GenAI and major clouds (AWS/GCP/Azure).
• Hands-on experience with LLMs, embeddings, RAG and prompt engineering.

Responsibilities

• Design, build, and deploy generative AI and ML solutions.
• Develop LLM-powered applications with RAG and tooling.
• Apply ML/DL to create AI tools solving business problems.
• Assist in traditional ML projects in CV, NLP, recommender systems.
• Stay updated on AI/ML trends and contribute to solution discussions.
• Grow AI/ML capabilities within the organization through mentoring.

Skills

ML/AI expertise

Python for ML

Cloud platforms

Production ML

LLM experience

Data engineering

Communication skills

Tools

Databricks

Snowflake

ML Ops tooling

Job description

Slalom is seeking a technologist to design, build, and deploy generative AI and ML solutions that address client business needs. You will develop LLM-powered applications with RAG, agents, and tool calling, and apply ML/DL to deliver practical AI tools. You’ll stay current with AI trends and contribute to mentoring and community growth.

You will bring 3+ years deploying models to production, plus 2-4 years in IT consulting, with strong communication and cloud fluency across AWS, GCP, or Azure.