AI/ML Engineer

Akaasa Technologies; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Akaasa Technologies seeks an experienced AI/ML Engineer to design, develop, and deploy production‑grade AI/ML solutions with a focus on Generative AI, LLMs, RAG, and agentic AI. You will build robust LLM‑powered applications and partner with product, clinical, and business teams to deliver impactful AI capabilities.

Ideal candidates have hands‑on experience in ML/AI pipelines, strong Python and software engineering practices, and a track record of delivering scalable AI systems in dynamic

Qualifications

• 5+ years building ML/AI systems with hands‑on LLMs or agentic apps.
• Strong ML/DL NLP, Generative AI, and transformer expertise.
• Proficiency in PyTorch and/or TensorFlow.

Responsibilities

• Design, develop, and deploy production‑grade AI/ML solutions.
• Collaborate with product, clinical, and business teams to deliver AI products.

Skills

Python

Transformer models

PyTorch

TensorFlow

LLM platforms

LangChain

RAG

SQL

Airflow

Docker

Kubernetes

Git/GitHub

Cloud platforms

Data pipelines

Education

Bachelor's or Master's in CS/DS

Tools

Databricks

Snowflake

Kafka

Terraform

PostgreSQL

SQL Server

Job description

AI/ML Engineer

Duration: 6 10 Months
Location: Remote (San Francisco, CA; Arlington, VA; Denver, CO; Chicago, IL; Boston, MA; New York, NY; Houston, TX; Miami, FL; Los Angeles, CA; Seattle, WA; Dallas, TX; Minneapolis, MN; Birmingham, MI; Atlanta, GA; or Irvine, CA)
Duration: 6 10 months
Interview: In‑person

Internal Note

• Must be local with DL copy
• Role is primarily remote, but candidates may be required to report to a local client office for ID verification during the project.
• LinkedIn with location and photo (before 2023)

Job Description

We are seeking an experienced AI/ML Engineer to design, develop, and deploy production‑grade machine learning and AI solutions, with a strong focus on Generative AI, Large Language Models (LLMs), RAG, and Agentic AI. The ideal candidate will have strong machine learning and software engineering fundamentals, hands‑on experience building LLM‑powered applications, and the ability to develop reliable AI solutions in collaboration with product, clinical, and business teams.

Required Qualifications

• 5+ years of experience building and deploying ML/AI systems, including recent hands‑on experience with LLMs or agentic applications.
• Strong expertise in Machine Learning, Deep Learning, NLP, Generative AI, and Transformer architectures.
• Experience with PyTorch and/or TensorFlow.
• Hands‑on experience with OpenAI/Azure OpenAI, Anthropic Claude, or comparable LLM platforms.
• Experience with prompt engineering, structured outputs, function/tool calling, and agentic frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent.
• Strong experience with RAG, vector databases, embeddings, retrieval, re‑ranking, grounding, and citation techniques.
• Familiarity with MCP (Model Context Protocol) or similar integration standards.
• Expert‑level Python skills and strong software engineering practices, including testing, Git/GitHub, code reviews, Docker, and CI/CD.
• Strong SQL skills and experience with SQL Server, PostgreSQL, or similar relational databases.
• Experience building data/ML pipelines and workflow orchestration using Airflow or equivalent.
• Experience working with unstructured and semi‑structured data at scale.
• Experience with AI/ML evaluation, observability, experiment tracking, and reproducibility. Familiarity with Arize, Langfuse, or comparable tools is a plus.
• Experience with Azure AI Services, Azure OpenAI, AWS SageMaker, or Google Vertex AI; Azure is preferred.
• Experience with Databricks, Snowflake, Spark, Kafka, Kubernetes, Terraform, and cloud‑native architectures is highly desirable.
• Strong understanding of Responsible AI, AI Governance, Model Risk Management, and AI Security.

Preferred Qualifications

• Experience working in healthcare, insurance, or other regulated/high‑stakes environments.
• Experience working with clinical or operational subject matter experts.
• Experience designing AI-assisted interfaces focused on trust, explainability, and evidence‑based review.
• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field, or equivalent practical experience.
• Strong communication skills with the ability to explain technical concepts and trade‑offs to both technical and non‑technical stakeholders.