Research Engineer, Machine Learning Job at Assessfirst (Palo Alto)

Research Engineer / Machine Learning Engineer - B2B Applications

OpenAI is at the forefront of artificial intelligence, driving innovation and sh...

Location

United States , San Francisco

Salary:

295000.00 - 445000.00 USD / Year

OpenAI

Expiration Date

Until further notice

Requirements

Master's/ PhD degree in Computer Science, Machine Learning, or a related field
2+ years of professional engineering experience (excluding internships) in relevant roles at tech and product-driven companies
Demonstrated experience in deep learning and transformers models
Proficiency in frameworks like PyTorch or Tensorflow
Strong foundation in data structures, algorithms, and software engineering principles
Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization
Excellent problem-solving and analytical skills, with a proactive approach to challenges
Ability to work collaboratively with cross-functional teams
Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines
Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done.

Job Responsibility

Innovate and Build: Design and build advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact
Collaborate with the Best: Work closely with software engineers, product managers and forward deployed engineers to understand complex business challenges, address customer concerns and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives
Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches
Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices
Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large.

What we offer

Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
401(k) retirement plan with employer match
Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
Mental health and wellness support
Employer-paid basic life and disability coverage
Annual learning and development stipend to fuel your professional growth
Daily meals in our offices, and meal delivery credits as eligible

Fulltime

Machine Learning Research Scientist / Research Engineer, Post-Training

Scale works with the industry’s leading AI labs to provide high quality data and...

Location

United States , San Francisco; Seattle; New York

Salary:

252000.00 - 315000.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field
Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning
Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning
Excellent written and verbal communication skills
Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
Previous experience in a customer facing role

Job Responsibility

Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities
Design and experiment new approaches to preference optimization
Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness
Publish research findings in top-tier AI conferences

What we offer

Comprehensive health, dental and vision coverage
retirement benefits
a learning and development stipend
generous PTO
equity based compensation
commuter stipend

Fulltime

Senior Machine Learning Engineer (Research Scientist) - Data Foundation & AI

We build simple yet innovative consumer products and developer APIs that shape h...

Location

United States , New York

Salary:

228960.00 - 315360.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

Strong applied ML research skills with production delivery experience
Depth in Transformers/LLMs, representation learning, or large-scale model training
Demonstrated ability to ship models to production (not just prototype)
Distributed training experience and strong Python + software engineering fundamentals
Fintech / financial data domain experience is a plus
External publications or open-source contributions is a plus

Job Responsibility

Building a foundation model on one of the world’s richest financial datasets that no one else has
Doing research that ships: moving from experimentation and prototypes to production systems serving real customers
Working across the full ML stack, from pretraining objectives and architectures to serving infrastructure and monitoring
Collaborating with a high-caliber team and seeing your work amplify the capabilities of multiple product teams
Helping hundreds of millions of consumers achieve greater financial freedom through data-driven products

Fulltime

Research Engineer - Machine Learning and Systems

We are hiring a principal level Research Engineer with deep strength in machine ...

Location

United States , New York City

Salary:

100000.00 - 250000.00 USD / Year

Helpcare AI

Expiration Date

Until further notice

Requirements

PhD in Computer Science, Machine Learning, Computer Graphics, Computer Vision, or related field, or equivalent research track record
Seven or more years of experience in applied ML or research engineering including significant time in fast paced or startup settings
Strong publication record in top venues such as NeurIPS, ICLR, ICML, CVPR, ECCV, ICCV, SIGGRAPH, or TOG with multiple first author papers or equivalent impactful artifacts
Proven experience training and serving large models at scale including multi GPU or multi node training, distributed data loading, mixed precision, and memory optimization
Fluency in Python and C++ and experience writing efficient CUDA or Triton kernels
Expertise with PyTorch or JAX and modern tooling for experiment tracking, evaluation, and deployment
Demonstrated ability to take ideas from paper to production with measurable impact on users or business outcomes
Strong systems skills including profiling, performance tuning, reliability engineering, and cost awareness
Excellent communication with the ability to work across research and product teams

Job Responsibility

Research, design, and implement models and systems across vision, generative modeling, simulation, rendering, and 3D perception
Build data, training, evaluation, and deployment pipelines with strong observability and reproducibility
Translate research insights into reliable production services that meet product and latency requirements
Contribute hands on across prototyping, optimization, integration, and scaling
Survey new methods and run grounded evaluations to identify what to adopt and when
Share expertise through design reviews, mentoring, and documentation

What we offer

Relocation support available

Fulltime

Senior Research Engineer Machine Learning, AI for Science

At Microsoft Research AI for Science we believe deep learning has the potential ...

Location

Germany , Berlin

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Completed MSc in computer science, machine learning, AI or a related area
Proficiency in collaborative software engineering in Python
Familiarity with Linux and the open-source ecosystem
In-depth understanding of open-source machine learning frameworks such as PyTorch and/or Jax
Experience in designing, developing and deploying ML systems
Experience building and optimizing distributed systems and large-data applications, including those using tensor accelerators or GPUs
Ability to work in an interdisciplinary collaborative environment, through effective communication of technical concepts to non-experts from different technical backgrounds

Job Responsibility

Develop and maintain tools, models and technologies for building, training, optimizing and scaling machine learning solutions
Architect, design, and implement scalable and robust solutions for machine learning and scientific research involving large volumes of heterogeneous data
Build and optimize distributed data processing and model building pipelines
Prepare and maintain open-source releases and releases for internal and external beta testers
Work cross-functionally with machine learning researchers, engineers and researchers from the natural sciences
Maintain high standards in code quality and software design
Document and share best practices across the organization

Fulltime

Search Machine Learning Research Engineer

Perplexity is seeking an experienced Senior Machine Learning Engineer to help bu...

Location

Germany , Berlin

Salary:

Not provided

Perplexity

Expiration Date

Until further notice

Requirements

Deep understanding of search and retrieval systems, including quality evaluation principles and metrics
Proven track record with large-scale search or recommender systems
Strong proficiency with PyTorch, including experience in distributed training techniques and performance optimization for large models
Expertise in representation learning, including contrastive learning and embedding space alignment for multilingual and multimodal applications
Strong publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, SIGIR)
Self-driven, with a strong sense of ownership and execution
Minimum of 3 years (preferably 5+) working on search, recommender systems, or closely related research areas

Job Responsibility

Relentlessly push search quality forward — through models, data, tools, or any other leverage available
Architect and build core components of the search platform and model stack
Design, train, and optimize large-scale deep learning models using frameworks like PyTorch, leveraging distributed training (e.g., PyTorch Distributed, DeepSpeed, FSDP) and hardware acceleration, with a focus on retrieval and ranking models
Conduct advanced research in representation learning, including contrastive learning, multilingual, and multimodal modeling for search and retrieval
Deploy models — from boosting algorithms to LLMs — in a scalable and performant way
Build and optimize RAG pipelines for grounding and answer generation
Collaborate with Data, AI, Infrastructure, and Product teams to ensure fast and high-quality delivery

Fulltime

Machine Learning Research Engineer

Internship program: 12 - 24 weeks, full-time, in-person in the Berlin office.

Location

Germany , Berlin

Salary:

Not provided

Perplexity

Expiration Date

Until further notice

Requirements

Understanding of search and retrieval systems, including quality evaluation principles and metrics
Strong proficiency with PyTorch, including experience in distributed training techniques and performance optimization for large models
Interested in representation learning, including contrastive learning, dense & sparse vector representations, representation fusion, cross-lingual representation alignment, training data optimization and robust evaluation
Publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, SIGIR)

Job Responsibility

Relentlessly push search quality forward — through models, data, tools, or any other leverage available
Train, and optimize large-scale deep learning models using frameworks like PyTorch, leveraging distributed training (e.g., PyTorch Distributed, DeepSpeed, FSDP) and hardware acceleration, with a focus on retrieval and ranking models
Conduct research in representation learning, including contrastive learning, multilingual, evaluation, and multimodal modeling for search and retrieval
Build and optimize RAG pipelines for grounding and answer generation

Fulltime

Machine Learning Research Engineer - Robotics

Scale’s Robotics business unit is dedicated to solving the data bottleneck in Ph...

Location

United States , San Francisco

Salary:

218400.00 - 273000.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

Practical experience building training VLA models and/or building robotics data
3+ years of relevant industry experience in areas relating to: robotics, computer vision, embodied AI, sim-to-real, imitation learning, reinforcement learning, and vision language actions models
PhD or equivalent experience in Machine Learning or Robotics
A track record of published research in robotics
Experience conducting data collection and performing evaluations
Strong written and verbal communication skills and the ability to work with cross-functional teams and customers
Intellectual curiosity, empathy, and ability to operate with a high degree of autonomy

Job Responsibility

Collaborate closely with Robotics customers to drive the industry forward in using VLA data
Develop ML pipelines to train/fine-tune models using Scale’s data
Conduct research on robotics data collection, cross-embodiment training, and policy fine-tuning
Develop novel methods for evaluating VLA models, including new robotics industry benchmarks
Partner with cross-functional stakeholders and Scale’s customers to improve data collection
Collaborate with product teams to bring ML outcomes to Scale’s platform

What we offer

Comprehensive health, dental and vision coverage
retirement benefits
a learning and development stipend
generous PTO
equity based compensation
may be eligible for additional benefits such as a commuter stipend

Fulltime

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Research Engineer, Machine Learning

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