Staff Research Engineer, Model Efficiency Job at Cohere

Senior Research Engineer, Model Evaluation

Evaluation is critical to making progress in scaling intelligence. As models con...

Location

United States; Canada; United Kingdom , Toronto; New York; Seattle; San Francisco; London

Salary:

Not provided

Cohere

Expiration Date

Until further notice

Requirements

You enjoy pushing the limits of what LLMs are capable of, and you have built high-quality evaluation resources to measure those capabilities (datasets, simulators, environments, etc.)
You have a track record of developing new methods and/or data to evaluate LLMs, e.g. publications at top-tier conferences, popular benchmarks, etc.
You have deep experience building with and around LLMs, and you have built tools for analyzing and understanding their performance
You have strong software engineering skills

Job Responsibility

Develop evaluation benchmarks, datasets, and environments for measuring the bleeding edge of model capabilities
Conduct research to push the state-of-the-art in LLM evaluation methods, including training LLM judges
improving evaluation efficiency
and scalably building high-quality datasets
Build scalable tools for investigating and understanding evaluation results that are used by all members of technical staff at Cohere, as well as leadership and our CEO
Learn from and work with the best researchers and engineers in the field

What we offer

An open and inclusive culture and work environment
Work closely with a team on the cutting edge of AI research
Weekly lunch stipend, in-office lunches & snacks
Full health and dental benefits, including a separate budget to take care of your mental health
100% Parental Leave top-up for up to 6 months
Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
6 weeks of vacation (30 working days!)

Fulltime

Staff Level Research Engineer, AI

Adyen is building a top-tier AI research engineering team to drive our next chap...

Location

Netherlands , Amsterdam

Salary:

Not provided

Adyen

Expiration Date

Until further notice

Requirements

10+ years of professional experience in software engineering, machine learning, or applied research, with a proven ability to drive high-impact initiatives end-to-end
Deeply plugged into the scientific AI research community and have a strong understanding of the latest advancements in AI, especially Generative AI (GenAI) and Large Language Models (LLMs)
Proven ability to take cutting-edge AI research papers and implement them into production-quality, scalable code
Strong engineering mindset with a track record of writing clean, efficient, and scalable code suitable for production environments
Excel at translating complex technical concepts into clear, understandable terms for diverse audiences, including engineers, executives, and during public events
Ability to think critically and deliver simple and elegant solutions to complex, cross-team problems, influencing strategic direction and fostering innovation across the organization
Excel in soft skills such as empathy, influence, negotiation, relationship building, and conflict resolution

Job Responsibility

Drive the execution of Adyen's AI research strategy, focusing on the practical application of Generative AI (GenAI) and other AI methodologies in finance
Bridge the gap between cutting-edge AI research and production by rapidly prototyping AI features and implementing research papers into robust, scalable, and production-ready code
Contribute to defining the long-term vision for AI at Adyen, specifically how AI will interact with humans and finance
Drive innovation by challenging the status quo, introducing transformative ideas, and leveraging technologies and methodologies to improve solutions
Carry out flexible, value-driven assignments, proactively unblocking teams, moving between teams or scopes as needed to maximize organizational impact
Provide technical mentorship and sponsorship to engineers across the organization
Connect with the broader AI community to stay informed of the latest advancements and identify potential partnership opportunities
Champion engineering and scientific alignment, advocate for high-quality standards, and drive the reduction of complexity and dependencies across teams
Actively pair with engineers to solve deep-rooted technical challenges and be fully capable of being hands-on with the code

Staff CV Applied Research Engineer, Edge AI

We are seeking a highly motivated and experienced Computer Vision Applied Resear...

Location

United States , Boston

Salary:

183300.00 - 268800.00 USD / Year

SimpliSafe

Expiration Date

Until further notice

Requirements

8+ years in applied ML/ML engineering, including shipping production CV models
Strong computer vision background with deep learning expertise across detection/classification/segmentation/tracking
Hands-on experience with vision transformers and/or DETR-style architectures, including practical knowledge of efficiency trade-offs for edge deployment
Demonstrated success deploying models in resource-constrained, real-time environments (embedded/mobile/IoT/edge)
Deep experience in model optimization: QAT/PTQ, distillation, pruning, compression, mixed precision, and hardware/runtime-aware training
Proficiency in Python and PyTorch and/or TensorFlow
ability to productionize models and collaborate with systems engineers (C++ experience strongly preferred)
Staff-level leadership: ability to drive ambiguous initiatives, align stakeholders, and mentor engineers

Job Responsibility

Lead end-to-end development of edge ML models for outdoor monitoring (e.g., person/vehicle/package detection, classification, tracking, segmentation, event understanding)
Architect, train, and deploy transformer-based vision models (e.g., compact ViTs, hierarchical transformers, DETR-style detectors) and hybrid CNN-transformer backbones optimized for embedded inference
Drive model efficiency through resource-aware design and training, including: Architecture: Token/patch reduction, efficient attention variants, early-exit / conditional compute
Training: distillation from large transformer teachers to edge students
Compression: Quantization (PTQ/QAT), pruning, mixed precision, and operator-aware optimization
Translate product requirements into model targets (accuracy, FPS, memory footprint, power/thermal) and ensure models meet budgets on doorbell/outdoor camera hardware
Partner with embedded/firmware and platform teams to integrate models into production pipelines
profile bottlenecks and improve end-to-end runtime performance
Define evaluation strategies tailored to outdoor edge deployments
perform failure analysis and improve long-tail robustness (nighttime, rain/snow, backlight, fast motion)

What we offer

A mission- and values-driven culture and a safe, inclusive environment where you can build, grow and thrive
A comprehensive total rewards package that supports your wellness and provides security for SimpliSafers and their families
Free SimpliSafe system and professional monitoring for your home
Employee Resource Groups (ERGs) that bring people together, give opportunities to network, mentor and develop, and advocate for change
Participation in our annual bonus program, equity, and other forms of compensation, in addition to a full range of medical, retirement, and lifestyle benefits

Fulltime

Member of Technical Staff, Integration/RL Team (Research Engineer)

The integration team is responsible for developing and scaling machine learning ...

Location

Salary:

Not provided

Cohere

Expiration Date

Until further notice

Requirements

Extremely strong software engineering skills
Value test-driven development methods, clean code, and strive to reduce technical debts at all levels
Proficiency in Python and related ML frameworks such as JAX, Pytorch and/or XLA/MLIR
Experience using and debugging large-scale distributed training strategies (memory/speed profiling)
[Bonus] Experience with distributed training infrastructures (Kubernetes) and associated frameworks (Ray)
[Bonus] Hands-on experience with the post-training phase of model training, with a strong emphasis on scalability and performance
[Bonus] Experience in ML, LLM and RL academic research

Job Responsibility

Design and write high-performing and scalable software for training models
Develop new tools to support and accelerate research and LLM training
Coordinate with other engineering teams (Infrastructure, Efficiency, Serving) and the scientific teams (Agent, Multimodal, Multilingual, etc.) to create a strong and integrated post-training ecosystem
Craft and implement techniques to improve performance and speed up our training cycles, both on SFT, offline preference, and the RL regime
Research, implement, and experiment with ideas on our cluster and data infrastructure
Collaborate, Collaborate, and Collaborate with other scientists, engineers, and teams!

What we offer

An open and inclusive culture and work environment
Work closely with a team on the cutting edge of AI research
Weekly lunch stipend, in-office lunches & snacks
Full health and dental benefits, including a separate budget to take care of your mental health
100% Parental Leave top-up for up to 6 months
Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
6 weeks of vacation (30 working days!)

Fulltime

Research Engineer, Core ML

This is a research engineering role with direct production impact. You will tran...

Location

United States , San Francisco

Salary:

200000.00 - 280000.00 USD / Year

Together AI

Expiration Date

Until further notice

Requirements

3+ years of experience working on ML systems, large‑scale model training, inference, or adjacent areas (or equivalent experience via research / open source)
Advanced degree in Computer Science, EE, or a related field, or equivalent practical experience
Demonstrated experience owning complex technical projects end‑to‑end
Strong expertise in at least one of the following: Large‑scale inference systems (e.g., SGLang, vLLM, FasterTransformer, TensorRT, custom engines, or similar), GPU performance, distributed serving
RL / post‑training for LLMs or large models (e.g., GRPO, RLHF/RLAIF, DPO‑like methods, reward modeling)
Model architecture design for Transformers or other large neural nets
Distributed systems / high‑performance computing for ML
Strong coding ability in Python
Experience profiling and optimizing performance across GPU, networking, and memory layers
Track record of impactful work in ML systems, RL, or large‑scale model training (papers, open‑source projects, or production systems)

Job Responsibility

Advance inference efficiency end‑to‑end
Design and prototype algorithms, architectures, and scheduling strategies for low‑latency, high‑throughput inference
Implement and maintain changes in high‑performance inference engines
Profile and optimize performance across GPU, networking, and memory layers
Unify inference with RL / post‑training
Design and operate RL and post‑training pipelines
Make RL and post‑training workloads more efficient with inference‑aware training loops
Co‑design algorithms and infrastructure
Run ablations and scale‑up experiments to understand trade‑offs
Own critical systems at production scale

What we offer

Startup equity
Health insurance
Competitive benefits

Fulltime

Senior Staff Engineer - Delivery Marketplace

Delivery Marketplace is a central pillar to Uber’s delivery products. As the cen...

Location

United States , New York

Salary:

267000.00 - 297000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

Bachelors (or higher) in relevant fields (Operations Research, Industrial Engineering, Computer Science, etc)
8+ years of industry experience developing algorithms and models for large-scale deployment
Experience with optimization packages such as Gurobi, CPLEX, Tools, etc
Strong communication skills and ability to work effectively with cross-functional partners
Proficiency in one or more coding languages such as Python, Java, Go, or C++

Job Responsibility

Work with a mixed team of Engineers, Applied Scientists, and Product Managers
Lead the design, development, optimization, and productization of solutions and systems that are used to solve strategically important or vaguely defined problems
Build solutions to improve Delivery marketplace efficiency while delivering magical user experience
Help set the team's technical direction and roadmap
Communicate with leadership, identify new opportunities, and help guide the growth of more junior engineers

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
All full-time employees are eligible to participate in a 401(k) plan
Eligible for various benefits

Fulltime

Staff Mechanical Engineer, Vacuum Systems

The Staff Mechanical Engineer, Vacuum Systems will work closely with Realta’s en...

Location

United States of America , Madison

Salary:

Not provided

Realta Fusion Inc.

Expiration Date

Until further notice

Requirements

BS in Mechanical Engineering, Materials Science, Aerospace Engineering, or a related field, plus 8+ years’ work experience
Extensive experience and expertise in 3D CAD design with current CAD software tools (SolidWorks, NX, Creo, etc.) and familiar with PDM
Demonstrated understanding of pressure vessel design, structural analysis, heat transfer, and thermal analysis, and the ability to leverage FEA tools such as ANSYS or COMSOL to solve engineering problems
Deep expertise of vacuum pump technologies (ion, turbomolecular, scroll, diffusion, cryogenically cooled panels, getters, etc…) and sealing and bakeout techniques for large vacuum chambers
Highly proficient in vacuum conductance and pump down modelling and optimization using tools such as MolFlow, VacTran, hand calculations, or other
Substantial technical experience with advanced knowledge and judgement in most of the following areas: Design, commissioning, and operation of ultra-high vacuum systems and parts compatible with vacuum environments
Welding, machining, and mechanical assembly processes and techniques
Project management abilities defined as the ability to control scope, cost, and schedule
Metrology, inspection, quality control, and test methods related to manufacturing using CMMs, laser trackers, FARO arms, or other test equipment
Demonstrated ability to supervise and safely direct activities of small teams of technical personnel

Job Responsibility

Collaborate with both physicists and scientists, as well as engineers and technical support staff, to develop technologies for novel vacuum systems requiring innovative designs and critical high-level analysis
Design and model complex ultra-high vacuum (UHV) pumping technologies, diagnostics, in-situ high temperature bakeout, sealing strategies, and vacuum vessels
Establish UHV best practices, design vacuum cleaning and handling laboratories, and mentor staff in UHV principles, contamination control, and leak detection
Design, build, and operate UHV test stands to validate both established and emerging vacuum technologies against stringent performance requirements
Research, select, and occasionally test UHV-compatible materials (e.g., low-outgassing metals, specific elastomers/metals for seals), specify cleaning protocols, and define bakeout and pump down sequences
Lead efforts involving general mechanical-system design, mechanical stress analysis, thermal analysis, and fatigue analysis
Interface with facilities and assist in the specification, design, and construction of a greenfield cryoplant and associated gas delivery systems
Conduct formal design reviews, generate technical documentation, and respond to questions concerning engineering design and operation
Work with vendors and internal resources to fabricate, assemble, test, and validate components and systems
Communication: Synthesize and present technical work internally and externally, communicate daily with project teams and leadership to support programmatic needs

What we offer

Competitive compensation package, including equity stock options
Comprehensive benefits including health, dental, and vision insurance, plus a retirement savings plan
Flexible paid time off (PTO) to support work-life balance
Work and live in Madison, Wisconsin — one of America’s most livable and vibrant cities

Fulltime

Staff Infrastructure Efficiency Analyst

As an Infrastructure Analyst within the Cloud C.O.R.E team you will be a key dri...

Location

United States , San Francisco

Salary:

211000.00 - 234000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

Ph.D., M.S. or Bachelor's degree in Economics, Statistics, Machine Learning, Operations Research, or other quantitative fields
7+ years of industry experience as an Applied or Data Scientist or equivalent (or 4+ years with Ph.D.)
5+ years of industry experience working with Cloud, either at a hyperscaler or as a cloud customer
Familiarity with cloud compute, storage, and data analytics concepts and products, demonstrated through either multiple years of experience on a team building cloud products, or managing the consumption of numerous cloud products, or through accreditation from numerous cloud certifications
Demonstrated experience mentoring and coaching junior analysts or peers, with ability to provide constructive feedback and support professional development
Excellent communication and collaboration skills: Able to lead initiatives across multiple areas and communicate findings with leadership and engineering teams
Background in at least one programming language (eg. Python, R, Java, Ruby, Scala/Spark or Perl)
Ability to use Python or similar technologies to work efficiently with large data sets and prototype algorithms & models
Coding and SQL proficiency and ability to develop statistical analysis and algorithm prototyping in Python or R
Fluency in MS Excel/Google Sheets for analysis and collaboration with finance teams

Job Responsibility

Translate complex cloud consumption data into actionable insights for leadership and engineering
Identify and track optimizations and realized savings
Establish key price-performance metrics and partner with engineering to implement price-performance optimizations within production scaling
Define and manage reporting of cloud consumption metrics and KPIs, ensuring transparency, accuracy, and accountability
Establish consumption anomaly detection capabilities and reporting
Partner with engineering and capacity planning teams to optimize resource consumption decision making
Support commitment strategies, ensuring commitment decisions that optimize spend and best serve the business and technical strategy
Embed cloud consumption shift-left principles into engineering design and architecture
Partner with engineers and business leaders to model future consumption and costs to drive strategic decision making
Collaborate on infrastructure demand planning across key infrastructure growth metrics

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
All full-time employees are eligible to participate in a 401(k) plan
Eligible for various benefits (see link)

Fulltime

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Staff Research Engineer, Model Efficiency

Job Description

Job Responsibility

Requirements

What we offer

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