What are the responsibilities and job description for the Applied Scientist position at Mindlance?
Job Details :
Job Title : ML Applied Scientist | ML Research Engineer
Job Duration : 12- month contract (Possibility for extension)
Job Location : Remote in New York NY
Description
Help us transform how machine learning and artificial intelligence systems are evaluated.
Our team conducts research, builds tools, and develops systems that help improve, refine, and scale evaluation.
We’re looking for technical staff members with strong backgrounds in applied AI / ML who are passionate about solving high-impact problems and advancing the state-of-the-art in the domain of evaluation.
This role will be multifunctional.
You will collaborate closely with highly skilled machine learning researchers and engineers, socio-technical research scientists, software engineers, and domain experts to help develop and deliver groundbreaking advances to mission-critical evaluation programs and methods.
We believe the most exciting problems in machine learning research arise at the intersection with real-world use cases and that this is also where the most critical breakthroughs come from.
In this role, you will identify and operationalize problems, prototype solutions, and deliver results.
As a ML Applied Scientist, you will
Become intimately familiar with product use cases, requirements, and data in order to develop the insights required for solving hard evaluation problems
Develop models and systems that reliably solve complex evaluation problems
Develop and refine benchmarks that help feature engineers advance the state-of-the-art
Research and develop methodological innovations that advance the state-of-the-art in AI evaluation
Collaborate on an applied R&D team that is oriented around principles of continuous delivery, iterative development, and fault tolerance
Minimum Qualifications
Substantive experience solving real-world problems with LLMs
Experience with LLM benchmarking and evaluation
Experience applying software engineering best practices to ML development
Strong research fundamentals
Substantive experience with one or more LLM training or post-training paradigm
Experience with PyTorch and / or MLX
Preferred Qualifications
Substantive experience with ML / AI development and evaluation, ideally in domains like natural language processing, natural language understanding, search, code generation, or language generation
Extensive experience using LLMs to solve downstream ML / AI development problems, such as synthetic data generation, auto-labeling, and data curation
Expertise in LLM fine-tuning and / or pre-training, bonus points for RL experience
PyTorch and / or MLX expertise
Publications in relevant conferences (NeurIPS, ICML, ACL, etc.) are a plus but not mandatory
Minimum Education & Experience
6 years of relevant industry experience with a Bachelor's degree; or 4 years with a Master's degree; or a PhD 3 years industry experience; or equivalent work experience.
EEO :
Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority / Gender / Disability / Religion / LGBTQI / Age / Veterans.”
