Representation learning jobs

Senior Data & AI Scientist

SD Solutions · Posted Nov 10, 2026

Open

Georgia, United States
Senior
6+ years

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Senior Data & AI Scientist

SD Solutions · Posted Nov 10, 2026

Open

Georgia, United States
Senior
6+ years

Apply with Referso

Senior Machine Learning Engineer (Fulfilment)

Grab · Posted Nov 10, 2026

Open

Singapore, Singapore
Senior
10+ years

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Lead the design and implementation of reinforcement learning and large language model systems for Grab's marketplace optimization, serving as a technical lead for a small team and reporting to the Head of Data Science.

Responsibilities

Design and implement end-to-end RL systems that combine model-based RL, offline RL, simulation, and online learning into a unified training pipeline.
Build latent world models and marketplace state representations that capture supply-demand interactions, location-based patterns, and behavioural signals from users and drivers.
Develop systems that optimize across multiple marketplace levers simultaneously—pricing, dispatching, and supply repositioning.
Create policy evaluation frameworks and establish monitoring systems that allow safe deployment of new decision-making policies in production.
Fine-tune open-source large language models on domain-specific data to build capabilities for prediction, reasoning, and simulation within marketplace applications.

Requirements

PhD in Computer Science, Operations Research, Applied Mathematics, or related field

Skills

Reinforcement Learning fundamentals Markov Decision Processes stochastic control

Quantitative Researcher - Machine Learning

Point72 · Posted Aug 15, 2024

Open

New York, New York, United States

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Quantitative researcher in the Cubist Machine Learning Research group, developing trading models using deep learning and NLP.

Responsibilities

Develop sophisticated trading models using machine learning
Manage all aspects of the research process including data ingestion, processing, analysis, methodology selection, implementation and testing
Prototype and evaluate model performance
Construct and develop features from raw data
Estimate effectiveness of features

Requirements

PhD in machine learning, computer science, statistics, or a related field
Nice to have: experience with sequential modeling
Nice to have: experience with translating mathematical models into code

Skills

deep learning time series forecasting deep neural networks representation learning machine learning software libraries such as TensorFlow or PyTorch Python R natural language processing technology TensorFlow PyTorch

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STAGIAIRE Data Scientist (H/F)

SERVIER MONDE · Posted Nov 10, 2026

Open

Gif-sur-Yvette, Île-de-France, France
Internship · Intern

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Stage de fin d’études en Data Science au sein de l’équipe Data Science & Data Management de l’institut R&D Servier à Paris‑Saclay, axé sur le Machine Learning pour l’optimisation de formats d’anticorps multispécifiques.

Responsibilities

Concevoir un générateur de données synthétiques reproduisant les caractéristiques clés de l’optimisation des formats d’anticorps
Réévaluer et affiner les méthodes de représentation numérique (embeddings) des architectures d’anticorps
Évaluer systématiquement les performances des modèles sur les données synthétiques
Simuler des stratégies de sélection de nouvelles architectures à tester et communiquer les résultats

Requirements

Master's degree
Bachelor's degree

Skills

Python Machine learning Statistics Probabilistic models Deep learning PyTorch GPyTorch

Machine Learning — PhD Intern (Variable Circuit, Place-and-Route, and Layout Representations)

Keysight · Posted Nov 9, 2026

Open

Barcelona, Barcelona
Internship · Intern

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Keysight is seeking a PhD intern to explore machine learning representations for variable electronic designs where the underlying structure can change across design points. The work extends beyond circuit topology to include physical layout, place-and-route structure, geometric relationships, connectivity, and design metadata used in modern electronic design workflows.

Responsibilities

Design and prototype graph-based and structured data encodings for variable electronic designs spanning circuit topology, physical layout, and place-and-route information.
Represent design attributes such as component or block identity, type, parameters, connectivity, placement, routing, geometry, hierarchy, and relevant constraints.
Analyze existing fixed-structure assumptions in data pipelines and identify where they limit generalization to new circuits, layouts, or routing patterns.
Develop mapping and validation utilities between source design data, such as netlists, layout representations, placement/routing metadata, and model-ready inputs.
Integrate representation prototypes with graph learning, surrogate modeling, and design optimization workflows.

Requirements

PhD in electrical engineering
PhD in computer engineering
PhD in computer science
PhD in applied mathematics
PhD in machine learning

Skills

Machine learning

Staff Machine Learning Engineer, Time Series & Statistical Methods - UK

Nominal · Posted Nov 9, 2026

Open

London, England, United Kingdom
On-site
Senior
8+ years

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Staff Machine Learning Engineer, Time Series & Statistical Methods

Responsibilities

Build anomaly detection, change-point detection, and forecasting for high-rate test and fleet telemetry.
Package these methods as agent tools, so our agents can run real feature engineering and statistics instead of guessing.
Develop signal-processing and statistical methods (frequency analysis, trend fitting, run-to-run comparison) that hold up on noisy, real-world data.
Partner with evals to measure when a method is good enough to put in front of engineers.
Set the technical bar and roadmap for ML at Nominal, including when, and whether, to invest in learned models over classical ones.

Requirements

Nice to have: anomaly detection or forecasting that drove real operational decisions
Nice to have: telemetry from aircraft, vehicles, energy systems, or robots
Nice to have: shipped ML methods as tools that other systems or agents call
Nice to have: worked with the latest models beyond text: VLMs, VLAs, multimodal transformers, or foundation models for robotics and physical systems

Skills

anomaly detection change-point detection

Postdoctoral Researcher in Data Science and Artificial Intelligence - BISS

Maastricht University · Posted Nov 6, 2026

Open

Heerlen, Limburg, Netherlands
Hybrid
Full-time · Senior
€5K–€7K per month

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Lead the data science and AI component of the VR-STRESS project, developing multimodal AI methods to infer user state for adaptive VR training.

Compensation

A gross monthly salary between €4925,00 and €6682,00 (based on full-time employment of 38 hours per week). 8% holiday allowance and an 8.3% year-end bonus.

Responsibilities

Develop methods for processing, integrating, and interpreting multimodal physiological and behavioral data
Build and evaluate robust and interpretable models of cognitive, emotional, and physiological user states
Translate models into real-time or near-real-time algorithms for adaptive VR applications
Collaborate closely with experimental psychologists, cognitive scientists, engineers, and VR developers
Disseminate results through scientific publications and conferences

Requirements

PhD in data science
PhD in artificial intelligence
PhD in machine learning
PhD in computer science
PhD in computational cognitive science

Skills

machine learning signal processing multimodal data fusion time-series analysis

Senior Data & AI Scientist

Senior Data & AI Scientist

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Requirements

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Senior Machine Learning Engineer (Fulfilment)

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Quantitative Researcher - Machine Learning

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Requirements

Skills

STAGIAIRE Data Scientist (H/F)

Responsibilities

Requirements

Skills

Machine Learning — PhD Intern (Variable Circuit, Place-and-Route, and Layout Representations)

Responsibilities

Requirements

Skills

Staff Machine Learning Engineer, Time Series & Statistical Methods - UK

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Requirements

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Postdoctoral Researcher in Data Science and Artificial Intelligence - BISS

Compensation

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