USA – Austin, Seattle

Job Overview

At Arm, we’re enabling the next wave of AI innovation - from cloud to edge, data center to device. Our AI Product Managers play a pivotal role in turning cutting-edge research and engineering into real-world solutions that scale across billions of devices. As part of a globally trusted ecosystem, you’ll define and shape products that power the future of intelligent, energy-efficient computing.

We’re looking for AI-focused Product Managers who thrive at the intersection of technology, strategy, and customer need - individuals who can align market trends with technical innovation, and help bring transformative AI products to life.

Responsibilities

As an AI Product Manager at Arm, your role may include: Defining and owning product roadmaps for AI/ML software, hardware, tools, or platforms Identifying emerging AI market opportunities and customer needs across domains Working closely with engineering, research, and design teams to guide product development Collaborating with business development and partner teams to support go-to-market strategy Ensuring delivery of impactful, scalable solutions aligned with Arm’s long-term vision

Required Skills and Experience

Demonstrated experience in product management, technical program management, or product strategy Familiarity with AI/ML technologies, platforms, or development workflows Strong ability to synthesize market trends, customer feedback, and technical input into clear product direction Excellent cross-functional collaboration and communication skills Ability to work across a range of stakeholders - from engineers to executives A strategic mindset with a drive to build products that solve real problems at scale

“Nice to Have” Skills and Experience

Experience with AI deployment in edge, embedded, cloud, or mobile environments Exposure to AI frameworks (e.g., TensorFlow, PyTorch), ML compilers, or hardware accelerators Background in developer tooling, ML model optimization, or platform product management Prior involvement in launching or scaling AI or infrastructure products

New York

Quantitative Researchers (QRs) specialize in a variety of areas, including but not limited to: using sophisticated data analysis skills to build predictive models, driving construction of a complex multi asset portfolio by utilizing large scale portfolio optimization techniques, and developing sophisticated optimization algorithms. Researchers with an exceptional record of achievement in their respective fields and a drive to apply quantitative techniques to investing are encouraged to apply to GQS.

Cupertino, California

Horizon Robotics (HKEX: 9660) is a leading provider of Smart Driving solutions for passenger vehicles, empowered by our proprietary software and hardware technologies. Our solutions combine cutting-edge algorithms, purpose-built software and processing hardware, providing the core technologies for smart driving that enhance the safety and experience of drivers and passengers. Horizon Robotics is key enabler for the smart vehicle transformation and commercialization with our integrated solutions deployed at scale.

The Silicon Valley Applied Research Lab is a research team located in Silicon Valley, dedicated to developing advanced algorithms and models for Advanced Driver Assistance Systems (ADAS), Autonomous Driving (AD) , and other generic robotics systems.

If you are looking for a role to explore, develop and innovate machine learning algorithms for AD and robotics technologies, you are welcome to join us.

Your Daily Practice

As an applied research scientist, you will take part in:

• Devising novel deep-learning based algorithms and converting them to prototypes of autonomous driving solutions, including but not limited to training foundation models, post-training with reinforcement learning, and world models.
• Practicing end-to-end machine learning skills, including data pipelining, model construction and fine-tuning, and comprehensive performance testing.
• Following closely with academia, identifying the latest trends and extending them to real industrial development.
• Publishing research papers in top notch conferences in machine learning domain.
• Showcasing the work via presentation in internal and external talks, conferences, and workshops.

What You Must Have

• PhD / MS degree in computer vision, machine learning or a related field with multiple research publications in top conferences or journals; alternatively equivalent years of industry experience solving CV problems which do not have readily available solutions.
• Expertise in at least one of these specific areas: deep learning-based perception, prediction and planning, vision-language models, and reinforcement learning.
• Track record of driving ML research projects from start to completion, including conception, problem definition, experimentation, iteration, and publication or productization.
• Strong programming skills in Python and/or C++.
• Extensive experience with ML frameworks such as PyTorch and Jax.
• Strong verbal and written communication skills.

Bonus points! - Track record in innovative solutions to real-world problems in machine learning domain. - Experienced with closed-loop methods in solving prediction and planning problems.

This is a hybrid role with the expectation of working at least 3 days per week in our Cupertino office. The base pay range for this full-time Applied Research Scientist position is between $150,000 and $300,000/year plus equity incentive, depending on your experience, qualifications, education, skills and other related factors.

This position is also eligible for an annual performance bonus and a competitive benefits package. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, Paid Holidays, Sick Days and Personal Time Off. We also sponsor H-1B visas and green card petitions.

Horizon Robotics is committed to be an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.

Toronto

Description - Bloomberg’s Engineering AI department comprises over 350 AI experts dedicated to building cutting edge, market-leading products. Leveraging advanced technologies including transformers, large language models, and dense vector databases, we are transforming search, discovery, and workflow solutions across the financial industry. As we expand our group, we are seeking highly skilled Machine Learning (ML) and Software Engineers who will contribute innovative solutions to AI-driven customer-facing products.

At Bloomberg, we foster transparency and efficiency in global financial markets. Our technology powers search and discoverability, bringing actionable insights from news, research, financial data, and analytics covering more than 35 million financial instruments. Since 2009, Bloomberg has been at the forefront of applying artificial intelligence to organize the vast volumes of structured and unstructured data that inform critical financial decisions, uncover market signals, and deliver clarity precisely when our clients need it most.

In Toronto, our Machine Learning Engineers are central to advancing Bloomberg’s efforts in financial query understanding and code generation. They bridge the gap between pioneering research and practical solutions, developing models to address complex financial queries and automate code writing. They engineer state-of-the-art code generation systems and apply LLM techniques like CoT, SFT or RLHF to drive iterative model refinement.

Join the AI Group as a Senior ML Research Engineer and you will have the opportunity to: -Collaborate with colleagues on production systems and write, test, and maintain production quality code -Design, train, experiment, and evaluate ML models, algorithms and solutions -Demonstrate technical leadership by owning cross-team projects -Stay current with the latest research in ML and incorporate new findings into our models and methodologies -Represent Bloomberg at scientific and industry conference and in open-source communities -Publish product and research findings in documentation, whitepapers or publications to leading academic venues

We are looking for Senior ML Research Engineers with the following experience: -Practical experience with solving Machine Learning problems and techniques -Ph.D. in ML, Statistics or a relevant field or MSc in CS, ML, Math, Statistics, Engineering, or related fields and 2+ years of relevant work experience -Experience with machine learning and deep learning frameworks -Proficiency in software engineering -An understanding of Computer Science fundamentals such as data structures and algorithms and a data oriented approach to problem-solving -Excellent communication skills and the ability to collaborate with engineering peers as well as non-engineering stakeholders. -A track record of authoring publications in top conferences and journals is a strong plus

San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US; Remote, US

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

We are looking for a Principal Machine Learning Engineer, a senior technical visionary, to be the Principal Technical Lead for our Content Engineering team setting up overall technical strategy, unified technical architecture and defining a roadmap for industry‑leading methodology. Strong hands-on machine learning background including deep learning architectures, generative AI, low-resource ML (zero shot, few shot), responsible AI and large scale deployment and measurement is required.

As the Principal Tech Lead for Content you'll be responsible for the technical direction, strategy and health of our Content Engineering org. You'll ensure that our technology can deliver on the business/product requirements necessary to keep Pinterest safe and positive. This means working with other leads to set and execute a long-term strategy for Trust, aligning the strategy with other clients where it makes sense and communicating to leadership our current status and path to having world-class Trust capabilities. You'll also foster a healthy community where all Trust engineers can learn best practices, collaborate effectively and understand our technical direction.

What you’ll do

• Develop strong partnerships with product teams to understand and proactively address future technology needs and current developer pain points.
• Champion and drive large-scale, cross-functional initiatives that improve the trust and safety of our platform.
• Act as the ultimate “customer representative” for engineers on Trust, including representing needs to leadership and prioritizing projects on the platform teams that ensure high quality capabilities and a world-class Pinner experience.
• Scale your leadership through both direct mentorship and via best practices, processes, training and tools.
• Ensure solid technical plans are in place for projects within Trust via direct review or delegation.
• Be the technical point of contact for decisions that impact the whole Pinterest platform and for cross-functional partners like policy, operations and legal.

What we’re looking for:

• Deep expertise building large scale ML systems at scale with modern frameworks.
• Knowledge of (and a passion for) building responsible and quality‑first discovery surfaces.
• Track record of delivering large, cross-functional projects across multiple organizations.
• Strong written and verbal communication skills and proven ability to collaborate cross-functionally.

About AIMATX

AIMATX is a Berkeley-based startup revolutionizing materials science by creating next-generation materials and molecules that power the future economy. Our AI-driven platform explores vast chemical spaces, predicts new materials and their properties, and accelerates discovery through intelligent, targeted experimentation. By reducing years of R&D to weeks, we are shaping the future of materials innovation;come join us!

AIMATX is built and guided by a world-class team at the intersection of science, AI and engineering. Our leadership includes Omar Yaghi (2025 Nobel Prize), Fernando Perez inventor of Jupyter/IPython, alongside former CEOs of public companies and leading researchers in generative AI and autonomous experimentation. This ecosystem brings unmatched scientific depth, computational expertise, and entrepreneurial excellence to accelerate the future of discovery.

Role Overview

We are seeking a highly skilled Computational Chemist / Materials Scientist to join our innovative team. You will apply your expertise in chemical and materials science R&D to develop sustainable, high-performance materials tailored to specific use cases. As part of our technical team, you will:

• Develop and apply AI-computational tools to predict novel material structures and properties.
• Design and implement machine learning algorithms to analyze large datasets and predict material behavior.
• Build AI-based methods for synthesis prediction of candidate materials.
• Collaborate with engineering teams to translate computational predictions into high-throughput experimental workflows.
• Incorporate experimental feedback into predictive models to improve accuracy within a closed-loop, self-improving platform.
• Analyze and visualize theoretical and experimental data, presenting insights to stakeholders and guiding research and product strategy.
• Work with data science experts to quantify and calibrate uncertainties across the predictive pipeline.
• Stay current with scientific advances and integrate relevant ideas into ongoing projects.
• Implement computational methods in a rigorously tested codebase deployed using modern software engineering best practices.

Required Qualifications

• PhD in Machine Learning, Computational Chemistry, Chemistry, Materials Science, Physics or a related field.
• Experience applying machine learning to scientific or structured data
• Proficiency with Python, GitHub workflows, testing, documentation, and continuous integration.
• Demonstrated leadership and project ownership in computational or ML-driven research.

Preferred Qualifications

• Experience developing modeling approaches, including physics-based atomistic modeling.
• Experience in polymer chemistry, ceramics, nanomaterials, or related areas.
• Publication record in peer-reviewed journals and presentations at scientific conferences.

Soft Skills & Cultural Fit

• Excellent written and verbal communication skills.
• Collaborative mindset and ability to work effectively in a multidisciplinary team.
• Strong organization, attention to detail, and a results-driven attitude.
• Proactive and self-motivated, with the ability to take initiative.
• Commitment to scientific rigor, innovation, and continuous learning.

Benefits & Perks

We offer a competitive salary with bonus potential and meaningful early equity. Compensation reflects experience, expertise and expected impact.

Additional benefits may include: - Flexible work arrangements and remote options. - Medical, dental, and vision coverage. - 401(k) with company matching. - Generous PTO and parental leave.

Equal Opportunity Statement

AIMATX is committed to fostering a diverse and inclusive workplace. All qualified applicants will receive consideration without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or vet

Send your CV to theo.jaf@aimatx.ai

Work Location:

Toronto, Ontario, Canada

Description

We are currently seeking talented individuals for a variety of positions, ranging from junior to senior levels, and will evaluate your application in its entirety.

Layer 6 is the AI center of excellence for TD Bank Group. We develop and deploy industry-leading machine learning systems that impact the lives of over 27 million customers, helping more people achieve their financial goals and needs. Our work spans the field of machine learning with areas such as deep learning and generative AI, time series forecasting and responsible use of AI. We have access to massive financial datasets and actively collaborate with world renowned academic faculty. We are driven to be at the cutting edge of machine learning in research, engineering, and impactful applications.

We are looking for world-class engineers to tackle cutting-edge problems in Machine Learning applied to the real world. Work with large-scale, real-world datasets spanning multiple modalities, ranging from banking transactions, conversation transcripts to large document collections.

As a Machine Learning Engineer, you will:

• Join a world-class team of AI developers with an extensive track record of shipping solutions at the cutting-edge

• Architect scalable machine learning and Gen AI systems that integrate with existing data platform and infrastructure, focusing on automation, operation efficiency, and reliability

• Write clean, efficient, and maintainable code for ML models to ensure efficient deployment of scalable AI application

• Work with large-scale, real-world datasets that range from banking transactions, conversation histories, to large document collections

• Grow by continuously learning new skills and exploring advanced topics in AI with a team that thrives on knowledge-sharing

Required Qualifications:

• Master or bachelor's degree in computer science, Statistics, Mathematics, Engineering or a related field

• 3+ years of developer experience shipping code in production settings

• Strong background in machine learning and deep learning

• Strong coding proficiency in Python, Java, C, or C++ You value good software design and sweat over details in code and API design

• You take great personal pride in building robust and scalable software

• You are highly accountable and have a strong sense of ownership

• You strive to communicate clearly and with empathy

Preferred Qualifications:

• Research experience with publication record

• Experience with LangGraph, Pytorch, Tensorflow, Jax, or comparable library

• Experience with building and scaling data-intensive software

• Experience using GPUs for accelerated deep learning training

ABOUT OUR TEAM

We are a remote-first team that sits across Europe and North America and comes together once a month in-person for 3 days and for longer offsites twice a year.

Our R&D and production teams are a combination of more research and more engineering-oriented profiles, however, everyone deeply cares about the quality of the systems we build and has a strong underlying knowledge of software development. We believe that good engineering leads to faster development iterations, which allows us to compound our efforts.

ABOUT THE ROLE

You would be working on our data team focused on the quality of the datasets being delivered for training our models. This is a hands-on role where your #1 mission would be to improve the quality of the pretraining datasets by leveraging your previous experience, intuition and training experiments. This includes synthetic data generation and data mix optimization.

You would be closely collaborating with other teams like Pre-training, Fine-tuning and Product to define high-quality data both quantitatively and qualitatively.

Staying in sync with the latest research in the field of dataset design and pretraining is key for being successful in a role where you would be constantly showing original research initiatives with short time-bounded experiments and highly technical engineering competence while deploying your solutions in production. With the volumes of data to process being massive, you'll have at your disposal a performant distributed data pipeline together with a large GPU cluster.

YOUR MISSION

To deliver massive-scale datasets of natural language and source code with the highest quality for training poolside models.

RESPONSIBILITIES

• Follow the latest research related to LLMs and data quality in particular. Be familiar with the most relevant open-source datasets and models
• Closely work with other teams such as Pretraining, Fine-tuning or Product to ensure short feedback loops on the quality of the models delivered
• Suggest, conduct and analyze data ablations or training experiments that aim to improve the quality of the datasets generated via quantitative insights

SKILLS & EXPERIENCE

• Strong machine learning and engineering background
• Experience with Large Language Models (LLM)
• Good knowledge of Transformers is a must
• Knowledge/Experience with cutting-edge training tricks
• Knowledge/Experience of distributed training
• Trained LLMs from scratch
• Knowledge of deep learning fundamentals
• Experience in building trillion-scale pretraining datasets, in particular: Ingest, filter and deduplicate large amounts of web and code data
• Familiar with concepts making SOTA pretraining datasets: multi-linguality, curriculum learning, data augmentation, data packing, etc
• Run data ablations, tokenization and data-mixture experiments
• Develop prompt engineering pipelines to generate synthetic data at scale
• Fine-tuning small models for data filtering purposes
• Experience working with large-scale GPU clusters and distributed data pipelines
• Strong obsession with data quality
• Research experience
• Author of scientific papers on any of the topics: applied deep learning, LLMs, source code generation, etc, is a nice to have Can freely discuss the latest papers and descend to fine details
• Programming experience: strong algorithmic skills, Linux Git, Docker, k8s, cloud managed services, Data pipelines and queues, Python with PyTorch or Jax Nice to have:
• Prior experience in non-ML programming, especially not in Python
• C/C++, CUDA, Triton

BENEFITS

• Fully remote work & flexible hours
• 37 days/year of vacation & holidays
• Health insurance allowance for you and dependents
• Company-provided equipment
• Wellbeing, always-be-learning and home office allowances
• Frequent team get togethers
• Great diverse & inclusive people-first culture

Location Seattle, WA, United States San Francisco, CA, United States

Description We are seeking a visionary leader to spearhead post training model research and development efforts. As the post training science lead, you will be responsible for driving the development and implementation of cutting-edge methodologies around improving model performance based on human feedback. You will lead a team of world-class scientists in exploring new frontiers of code generation for the most popular languages simplifying documentation, unit testing, optimizing existing code, explaining code and simplifying way users interact with the database systems enabling natural language interface. Responsibilities

Responsibilities

Research and Development: Conduct in-depth research on code generation techniques, including code to code (Java, SQL, Python, etc.), doc to code/code to doc, and other emerging approaches. Model Development: Design, develop, and train state-of-the-art code generation models that meet the highest quality standards. Team Leadership: Build and mentor a high-performing team of scientists and engineers. Collaboration: Work closely with cross-functional teams to integrate code generation capabilities into various applications and products. Innovation: Identify new opportunities for image generation and explore emerging technologies. Stay Updated: Maintain a deep understanding of industry trends and advancements in code generation.

Qualifications and Experience:

PhD Computer Science, Mathematics, Statistics, Physics, Linguistics or a related field with a dissertation, thesis or final project centered in Machine Learning and Deep Learning) with 5+ years relevant experience is preferred but not a must; OR Masters or Bachelor’s in related field with 8+ years relevant experience Strong publication record, including as a lead author or reviewer, in top-tier journals or conferences. Extensive experience in image generation, computer vision, and deep learning Proven track record of leading research and development projects Strong understanding of machine learning algorithms and architectures Excellent problem-solving and analytical skills Strong leadership and communication abilities

If you are passionate about pushing the boundaries of image generation and have a proven track record of success, we encourage you to apply. Qualifications Disclaimer:

Certain US customer or client-facing roles may be required to comply with applicable requirements, such as immunization and occupational health mandates.

Range and benefit information provided in this posting are specific to the stated locations only

US: Hiring Range in USD from: $120,100 to $251,600 per annum. May be eligible for bonus, equity, and compensation deferral.

Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle’s differing products, industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity.

Oracle US offers a comprehensive benefits package which includes the following: 1. Medical, dental, and vision insurance, including expert medical opinion 2. Short term disability and long term disability 3. Life insurance and AD&D 4. Supplemental life insurance (Employee/Spouse/Child) 5. Health care and dependent care Flexible Spending Accounts 6. Pre-tax commuter and parking benefits 7. 401(k) Savings and Investment Plan with company match 8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for sub

About Kumo.ai

Kumo.ai is redefining enterprise AI with foundation models for relational data, enabling organizations to predict, optimize, and act with speed and confidence.
Our mission is simple yet ambitious: make the world’s most important data also its most useful.

At Kumo, we are committed to building cutting-edge products that are also intuitive and easy to use. Our work blends deep technical innovation with thoughtful user-centric design.

Our Culture

We foster an inclusive, collaborative culture where every individual contributes to our shared mission.
We value:

• Diversity of thought
• Open and transparent communication
• Working together to solve meaningful problems
• Serving our customers with excellence
• Building a supportive and thriving community

We’re Hiring

We are looking for ML/AI Engineers with experience in one or more of the following:

• Graph Neural Networks (GNNs)
• Graph Transformers
• Agentic Frameworks
• Applied Machine Learning

If you're excited about building the next generation of AI for relational data, we’d love to talk.