AL/ML Engineer

TaskVerse; United States; On-site; USD 140,000 - 210,000; Full time

Job summary

Info Way Solutions LLC in Santa Clara, CA seeks an AI/ML Engineer to develop and deploy machine learning solutions from research to production, including building LLM-based systems and evaluation pipelines.

Ideal candidates have at least two years of ML or data science experience, a track record of production-ready models, and ability to collaborate with engineering and product teams to balance model quality, latency, and scalability.

Qualifications

• At least two years of experience in machine learning or data science with production ML
• Strong understanding of ML/deep learning concepts and practical experience with common libraries
• Experience shipping ML systems for production use

Responsibilities

• Design, train, test, and deploy ML models for reliable use at scale
• Develop LLM-based systems, including fine-tuned models, agent workflows, and evaluation pipelines
• Collaborate with engineering and product teams to scope problems and define success criteria and evaluation frameworks

Skills

Machine learning

Deep learning

Production ML

LLM experience

Python

Education

Bachelor's degree in CS/ML

Tools

scikit-learn

Keras

TensorFlow

PyTorch

Theano

DyLib

Job description

About The Company

Info Way Solutions LLC is seeking an AI/ML Engineer to help develop and deliver machine learning solutions for real-world applications. This opportunity is suited to an engineer who enjoys working at the intersection of research and product development, where ideas are tested, refined, and translated into dependable systems. The role offers the chance to contribute to end-to-end machine learning initiatives, including model development, evaluation, deployment, and ongoing improvement.

About The Role

This is a full-time, direct-hire opportunity based in Santa Clara, California. The ideal candidate is a junior- to mid-level professional with at least two years of experience in machine learning or data science and a track record of bringing machine learning systems into production. You will build and deploy models at scale and work on large language model (LLM) applications, including fine-tuning, agent development, and evaluation pipelines. The role calls for someone who can move comfortably between experimentation and production-grade engineering, collaborate across teams, and make practical decisions that balance model quality, latency, and scalability. Local Bay Area candidates are preferred.

Qualifications

Applicants should have at least two years of relevant experience in machine learning, data science, or a closely related field, including experience shipping ML systems for production use. Candidates should demonstrate a strong understanding of machine learning and deep learning concepts and practical experience with one or more commonly used libraries, such as scikit-learn, Keras, TensorFlow, PyTorch, Theano, or DyLib.

We are particularly interested in candidates with deep expertise in at least one area: search, retrieval, ranking, or recommendation systems; generative AI product development; LLM agent products; or LLM fine-tuning. Experience should extend beyond prototypes or demonstrations and include sound problem scoping, evaluation, and attention to how systems perform in practice. Applicants should understand common LLM limitations, including bias, hallucinations, and knowledge cutoffs, and be prepared to address these issues through appropriate design and evaluation approaches.

Experience at an early-stage startup or contributing to a product launch from concept to initial release is valuable. A strong academic or equivalent technical foundation is welcome; however, practical skills, sound engineering judgment, and demonstrated results are central to the role. Candidates should be comfortable communicating technical trade-offs and working with both engineering and product colleagues.

Responsibilities

Design, train, test, and deploy machine learning models for reliable use at scale. Develop LLM-based systems, including fine-tuned models, agent workflows, and repeatable evaluation pipelines. Partner with engineering and product teams to understand user and business needs, scope technical problems, define measurable success criteria, and establish robust evaluation frameworks.

Identify and mitigate model risks, including bias, hallucinations, and limitations associated with training data or knowledge cutoffs. Improve model performance and system behavior through careful experimentation and iteration. Optimize solutions for accuracy, latency, scalability, and reliability in real-world environments. Contribute throughout the product lifecycle, from research and prototyping through deployment, monitoring, and ongoing refinement. Document findings and communicate results so that teammates can make informed decisions.

Benefits

This full-time, direct-hire role offers the opportunity to work on practical AI/ML products and contribute across the development lifecycle. The position provides hands-on exposure to machine learning, deep learning, and generative AI challenges, with opportunities to collaborate across technical and product disciplines. Specific compensation, benefits, and work-arrangement details can be discussed during the hiring process.

Equal Opportunity

Info Way Solutions LLC is committed to fair and inclusive hiring. Candidates will be considered based on relevant qualifications, skills, experience, and potential. We welcome applicants from diverse backgrounds and encourage all qualified individuals to apply.