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.

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 9 days ago on Joblaze — tracked directly from Fundamental's career page.
Fundamental has 17 other open roles including MLOps Team Lead, Full-Stack Engineer, Solutions Architect.
6536 active Python roles on Joblaze right now.
1682 active AI roles on Joblaze right now.
797 active Machine Learning roles on Joblaze right now.
Typical Python salary we track runs $125,000–$190,800 (median $160,000, across 3234 roles). See Python salary trends

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

About Fundamental

Fundamental is an AI company pioneering the future of enterprise decision-making. Founded by DeepMind alumni, Fundamental has developed NEXUS – the world's most powerful Large Tabular Model (LTM) – purpose-built for the structured records that actually drive enterprise decisions. Backed by world class investors and trusted by Fortune 100 companies, Fundamental unlocks trillions of dollars of value by giving businesses the Power to Predict.

At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI.

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

Nice to have

Expertise within one of the following areas is a strong bonus: Architecture Research, Distillation (Model Compression), Evaluation, Code Generation, LLMs
Experience with foundational models, e.g. LLMs
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
Comprehensive health coverage for you and your dependents
Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys
Relocation support for employees moving to join the team in one of our office locations
A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action