ML Researcher
Join Fundamental as an ML Researcher to tackle groundbreaking challenges in AI model development for enterprise decision-making.
Posted by employer 12 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 20 hours ago
Skills & Technologies
AI in the day-to-day
Your work will focus on the entire lifecycle of the models, contributing to ideation, designing, implementing, and evaluating ML models.
Requirements
- Education
- Master's degree
Not disclosed in this posting: compensation, years of experience, work arrangement, visa sponsorship.
Benefits
Joblaze summary
In this role, the ML Researcher at Fundamental engages in the entire lifecycle of machine learning model development, focusing on ideation, implementation, and evaluation of innovative models for enterprise applications. Proficiency in Python and familiarity with ML frameworks are essential, along with a solid understanding of software engineering principles and experience in scaling models. This position is ideal for individuals with a strong background in machine learning research, particularly those who have contributed to foundational models or have published work in AI. Fundamental fosters a collaborative environment that emphasizes rapid development and testing of new ideas.
Joblaze insights
- Listed about a month ago — first seen on Joblaze September 3, 2026. Last confirmed on Fundamental's careers page October 27, 2026.
- Python appears in 47.2% of 832 comparable mid ai/ml roles; ML infrastructure appears in 0.2% of 832 comparable mid ai/ml roles.
Quick facts
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AI, Deep Learning, ML infrastructure, Machine Learning, Python.
- What seniority level is this role?
- Fundamental targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this ML Researcher role at Fundamental.
From the original posting
Key responsibilities
As part of the Research team, you will contribute to ideation, designing, implementing, and evaluating breakthrough Machine Learning models that will be deployed in the real world. Your work will be focused on the entire lifecycle of the models. Alongside the rest of the ML researchers in the team, you will be responsible for our models’ performance in every meaning of this word - whether this means achieving high evaluation scores through novel architectures and training methods, establishing the evaluation protocols themselves, or implementing methods that allow for efficient training and inference. The greatest research is done through solid engineering, so alongside the research you will also take part in ensuring that our research code allows swift, rapid development and testing of new ideas - both your own and the rest of the team’s.
Must have
Strong familiarity with the full research cycle in Machine Learning
Strong fundamentals of software engineering
Strong knowledge of Python, and its ML frameworks
Experience with:
Full lifecycle of AI model development
ML infrastructure frameworks and tools
Developing new ML methods, algorithms and models
GPUs (or TPUs) and distributed training
Scaling up models and training regimes
Knowledge of:
Classical ML methods and algorithms
Deep Learning techniques
Expertise in at least one of the following:
Tabular models, time series models, relational foundation models, structured data, large-scale foundation models
Nice to have
Published research at AI conferences
Contributions to open source ML projects
Experience working with tabular data / predictive analytics
High Kaggle rank
BSc/MSc/PhD in computer science/machine learning
Benefits
Competitive compensation with salary and equity
Standard company text repeated across Fundamental's postings is omitted here.