What are the responsibilities and job description for the Senior Data + ML Engineer (Generative AI with Fine-Tuning focus) position at InfoVision, Inc.?
Job Details
Job Summary
We are seeking a highly skilled and experienced Senior Machine Learning Engineer with a strong background in data science, machine learning, and generative AI. In this role, you will work closely with clients to build, fine-tune, and deploy locally hosted Small Language Models (SLMs) tailored for specific business use cases such as billing tasks and FAQs. You will be instrumental in refining models using curated datasets, fine-tuning techniques, and benchmarking performance to deliver cutting-edge AI solutions.
Key Responsibilities
- Work with our center of excellence for GenAI on creating groundbreaking solutions and conquering challenging projects.
- Build, fine-tune, and optimize locally hosted SLMs using curated golden questions and answers.
- Leverage expertise in models such as BERT, SBERT, and other transformer architectures to enhance language model performance.
- Design and execute fine-tuning workflows for both on-premises (NVIDIA A100 GPUs or similar) and cloud-based environments.
- Develop benchmarking frameworks to track model performance, quantify results, and establish measurable improvement metrics.
- Identify key parameters to evaluate and improve performance across various value driven use cases.
- Apply best practices in data refinement and preprocessing to ensure high-quality input for training and fine-tuning.
- Stay updated with the latest advancements in generative AI and machine learning technologies to incorporate innovative approaches.
- Collaborate with cross-functional teams, including data scientists, engineers, and non-technical stakeholders, to deliver effective AI solutions.
Qualifications
- Experience: Overall 10 years of experience & 7 years in data science and machine learning.
- Technical Expertise:
- Proven track record with transformer models (e.g., BERT, SBERT) and generative AI technologies.
- Experience with LLMs and SLMs, particularly in fine-tuning and deploying on-premises and cloud environments.
- Familiarity with GPU setups like NVIDIA A100s for model training and optimization.
- Data Science Skills:
- Strong fundamentals in data refinement, preprocessing, and quality assurance.
- Proficient in designing benchmarking processes, tracking performance, and tying results to numerical metrics.
- Ability to identify and optimize key performance parameters for specific use cases.
- Communication Skills: Excellent verbal and written communication skills, with the ability to clearly articulate complex technical ideas to diverse audiences.
- Education: Bachelor's or Master s degree in Computer Science, Data Science, Machine Learning, or a related field.
Preferred Skills
- Experience with fine-tuning LLMs/SLMs in enterprise environments.
- 1-2 years of research-focused work for LLM / benchmarking.
- Familiarity with benchmarking tools and frameworks for performance evaluation.
- Hands-on experience working with data integration and model deployment pipelines.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
