Generative AI & ML Engineer for Rapid Prototyping

Ness Digital Engineering; Location (WV); On-site; USD 32,000 - 39,000; Full time

Benefits offered by this job

Training & Certifications

Bonuses

Social activities

Competitive compensation

Job summary

Ness Digital Engineering is seeking a Data Scientist with an interest in Generative AI, LLMs, Machine Learning, and agentic systems. You will join an Advanced Solutions team focused on applied AI research, rapid prototyping, and turning innovative ideas into real business solutions.

Expect a startup-like environment with high-level challenges and ownership from idea to implementation. Collaborate with a small international team, design and test AI components, and contribute across the full

Qualifications

• 2–5 years of experience in AI, ML, or Data Science.
• Hands-on experience with Python; PySpark and SQL are a plus.
• Interest in Generative AI, LLMs, and agentic systems.

Responsibilities

• Reinvent how insights are shared and consumed by customers.
• Enable hyper-personalization and natural interaction for fleet operations.
• Support data-driven decision making for fleet managers.
• Design and build AI components to improve predictive models.
• Prototype, test, and iterate on AI/GenAI solutions.
• Collaborate across full lifecycle from problem to deployment.
• Explore emerging AI technologies and modern frameworks.
• Work with a small international team to solve business challenges.

Skills

AI

Machine Learning

Data Science

Python

PySpark

SQL

Tools

LangChain

LangGraph

MCP

Agentic AI

Job description

Ness Digital Engineering is seeking a Data Scientist with an interest in Generative AI, LLMs, Machine Learning, and agentic systems. You will join an Advanced Solutions team focused on applied AI research, rapid prototyping, and turning innovative ideas into real business solutions.

Expect a startup-like environment with high-level challenges and ownership from idea to implementation. Collaborate with a small international team, design and test AI components, and contribute across the full