MLSys 2026 Career Opportunities

About Unconventional

Since 2022, AI has entered the mainstream, reshaping entire industries from education and software development to fundamental consumer behaviors. This revolution has created an unprecedented demand for computation - a demand that is now fundamentally limited by energy, not just in the datacenter, but at a global scale.

At Unconventional, our mission is to solve this. We are rethinking computing from the ground up to build a new foundation for AI that is 1000x more efficient. We're doing this by exploiting the rich physics of semiconductors, mapping neural networks directly to the device physics rather than relying on layers of inefficient abstraction.

The Role

As a Member of Technical Staff, Language & Reasoning Models, you will drive the development of foundational language and reasoning models that fundamentally leverage the dynamics of our novel silicon. Your goal is to map the behaviors of modern language models directly onto the physics of our hardware.

You will sit at the intersection of NLP/reasoning research and hardware codesign, proving that high-fidelity, large-scale language understanding and generation can be achieved natively on an unconventional computing substrate.

What You'll Do

• Model Development: Design, train, and scale next-generation language and reasoning architectures (such as transformers, state space models, diffusion/flow models, and deep equilibrium models) specifically tailored for unconventional compute.
• Physics-Informed Architecture: Rethink standard sequence modeling to exploit the continuous-time dynamics of silicon, moving away from layers of inefficient digital abstraction. 
• Evaluation & Scaling: Establish the training recipes, loss functions, and evaluation metrics needed to reach the frontier of language comprehension, logical reasoning, and generation speed while maintaining the massive energy efficiency of our platform.
• Extreme Codesign: Collaborate with hardware designers and theorists, and system builders to co-design the model architecture alongside the underlying physical compute primitives.  

Minimum Qualifications

• Education: An MS/PhD or equivalent research/project experience in a quantitative field such as AI/Machine Learning, Computer Science, Physics, Electrical Engineering, or Applied Math.
• Experience:  Deep, hands-on expertise in the theory, architecture, and training of modern foundation models (transformers, SSMs, text diffusion/flow, etc.).
• Systems Fluency: Hands-on, battle-tested experience dealing with model scaling. You have successfully designed and executed full-scale, distributed training runs for large language or reasoning models, managing the complexities of massive compute clusters.
• Software Development: You are fluent in modern deep learning frameworks (PyTorch or JAX) and have a proven track record of writing clean, scalable training code for large language models.

Preferred Qualifications (Nice to Have)

• Unconventional Experience: As a bonus, you may have experience working with hardware-in-the-loop training, mixed-signal hardware, quantization, or physics-informed neural networks

Why Join Us?

• The Mission: Redefine computing for the next 50 years by solving the fundamental energy limitation of AI at a global scale.
• The Impact: Shape the company's future as a foundational team member. Enjoy massive ownership and an outsized opportunity to drive change.
• The Perks: A comprehensive package including best-in-class health benefits, 401k matching, truly unlimited PTO, and complimentary meals in our Palo Alto office.

Location Santa Clara, California US or Toronto, Canada

Description At Lemurian Labs, we’re on a mission to bring the power of AI to everyone—without leaving a massive environmental footprint. We care deeply about the impact AI has on our society and planet, and we’re building a rock-solid foundation for its future, ensuring AI grows sustainably and responsibly. Because let’s face it, what good is innovation if it doesn’t help the world?

We are building a high-performance, portable compiler that lets developers “build once, deploy anywhere.” Yes, anywhere. We’re talking about seamless cross-platform compatibility, so you can train your models in the cloud, deploy them to the edge, and everything in between—all while optimizing for resource efficiency and scalability.

If the idea of sustainably scaling AI motivates you and you’re excited about making AI development both powerful and accessible, then we’d love to have you. Join us at Lemurian Labs, where you can have fun building the future—without leaving a mess behind.

Here is what you will do: - Design, develop, maintain and improve our heterogeneous AI compiler. - Design and implement new capabilities in our compiler based on our novel compiler architecture. - Propose improvements to and expansions of our novel compiler architecture with respect to new advancements in machine learning model architectures and hardware. - Use the latest techniques in parallelization and partitioning to automate generation and exploit highly optimized kernels. - Generate and use performance data to identify opportunities and drive improvements. - Work with our product team to understand the evolving needs of ML engineers and drive improvements in architecture.

Essential Skills and Experience: - BS degree in computer science, computer engineering, electrical engineering, or equivalent practical experience - 4+ years of experience working with compilers. - Very strong knowledge of compiler algorithms and data structures. - Experience and interest in low level code generation, object file manipulation and target specific optimizations - 4+ years of experience with C/C++ - Strong written and oral communication, and able to write clear and concise documentation - Team first attitude - Detail oriented

Preferred Skills and Experience: - Masters or PhD degree in computer science, computer engineering, electrical engineering, or equivalent practical experience. - Knowledge of traditional compiler techniques; instruction selection, register allocation and traditional analysis like dominance, def-use et al. - Knowledge of calling conventions and APIs, linking and relocations. - Working knowledge of LLVM. - Experience with loop optimizations (vectorization, unrolling, fusion, parallelization, etc). - Experience with machine learning workloads and their demands on hardware.

Salary depends on experience and geographical location.

This salary range may be inclusive of several career levels and will be narrowed during the interview process based on a number of factors, such as the candidate’s experience, knowledge, skills, and abilities, as well as internal equity among our team.

Additional benefits for this role may include: equity, company bonus opportunities, medical, dental, and vision benefits; retirement savings plan; and supplemental wellness benefits.

Lemurian Labs ensures equal employment opportunity without discrimination or harassment based on race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, age, disability, national origin, marital or domestic/civil partnership status, genetic information, citizenship status, veteran status, or any other characteristic protected by law.

EOE

We’re looking for excellent developers to join our growing Software Engineering organization.  Our work is collaborative, and our hiring reflects that. Interviewing at PDT is focused less on filling a specific role, and more on finding great people who can build long-term, varied careers with us.

Software Engineers at PDT are responsible for building and maintaining the technology the enables all parts of the trading life cycle, including building the trading systems, risk controls and post-trade technologies.

We are looking for people that can add to a company that values creativity, energy and problems that are solved by collective thinking. We are focused, deliberate, but nimble. We want our people to have the freedom to assess and then solve the challenging problems they are faced with independence and agility. This gives them an opportunity to make a direct impact on our bottom line. For the right talent, PDT offers fantastic growth potential.  

This is a hybrid position and will require the person to work from our New York City office at minimum 3 days a week.

Why join us? 

PDT Partners has a stellar 30+ year track record and a reputation for excellence. Our goal is to be the best quantitative investment manager in the world—measured by the quality of our products, not their size.  PDT’s very high employee-retention rate speaks for itself.  Our people are intellectually extraordinary, and our community is close-knit, down-to-earth, and diverse.  

Responsibilities:

Partner with internal end-users to understand (and anticipate) new features and requirements, then engineer efficient and effective solutions.

Develop and maintain our proprietary software stack using C++, Python, and Java.

Identifying, assessing, deploying the latest open-source and third-party software in both an on-prem and cloud environment.

Below is a list of skills and experiences we think are relevant. Even if you don’t think you’re a perfect match, we still encourage you to apply because we are committed to developing our people.

Significant experience programming in one or more of C++, Python, or Java. Experience working directly with users or clients, capturing requirements, and scoping Ability to participate in the design of complex software systems and select prudent and pragmatic technologies to fit the business objective.

Experience working with trading systems or financial data, working with low-latency systems, or working in a data science- or research-adjacent role a plus.

Education:

Bachelor’s or master’s degree in computer science

The salary range for this role is between $160,000 and $200,000. This range is not inclusive of any potential bonus amounts. Factors that may impact the agreed upon salary within the range for a particular candidate include years of experience, level of education obtained, skill set, and other external factors.

PRIVACY STATEMENT: For information on ways PDT may collect, use, and process your personal information, please see PDT’s privacy notices.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.

Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.

Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.

Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI.

The Ideal Candidate:

You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.

Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.

You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example.

You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.

You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.

You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

The D. E. Shaw group seeks a machine learning researcher to creatively apply their knowledge of ML and software engineering to design and build computational architectures for high-performance, large-scale knowledge discovery in financial data. In this dynamic role, the engineer will leverage cutting-edge ML research to turn new ideas into proof-of-concept implementations, solve tough low-level engineering problems, and set up infrastructure for broader, longer-term impact. This position will play a key role in improving the efficiency, scalability, and reliability of the firm’s ML efforts, and will directly impact the firm’s systematic research through ML engineering contributions, all within a collaborative and engaging environment.

What you'll do day-to-day

• Rapidly prototype, implement, and evaluate state-of-the-art machine learning techniques.
• Drive the computational agenda for ongoing and future ML projects.
• Tackle complex engineering problems across software and hardware layers, setting technical direction and anticipating architectural needs.
• Deploy ML models into real-world systems where they have direct, measurable impact on decision-making and trading.
• Create compelling proof-of-concept systems, demonstrate them internally, and collaborate with others for development.
• Partner with researchers to design and implement efficient training workflows, enabling rapid experimentation with deep learning models.

Who we're looking for

• Bachelor’s degree or higher is required.
• Proven track record of collaborating with researchers to translate ML ideas into high-performance solutions.
• Experience driving computational and architectural innovation by rapidly prototyping and demonstrating novel ML ideas within a high-performance environment.
• Interest in staying current with ML research and swift application of new techniques.
• Expertise in performance optimization, low-level engineering, GPU programming and libraries (e.g., Pytorch, JAX, CUDA, XLA, Triton, or PTX).
• Demonstrated ability to quickly solve complex computational problems, create inspiring technical demos, and transition work to broader teams.
• Proactive approach in driving agendas and anticipating engineering bottlenecks in large systems.
• Proficiency in modern ML frameworks, facility with deep learning tooling, and a solid understanding of hardware and architectural challenges.
• The expected annual base salary for this position is $275,000 to $350,000. Our compensation and benefits package includes substantial variable compensation in the form of a year-end bonus, guaranteed in the first year of hire, a sign-on bonus, and benefits including medical and prescription drug coverage, 401(k) contribution matching, wellness reimbursement, family building benefits, and a charitable gift match program.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to manage information at a massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

In this role, you will design the new intelligence layer of the Search’s growth ecosystem with a new long-term life-cycle model.In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve engineering issues and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

The US base salary range for this full-time position is $174,000-$252,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities Design and deploy advanced models (e.g., Contextual Bandits, Transformers, Sequence Modeling) to optimize promo inventory by leveraging on multi-headed objective functions that balance growth goals against user annoyance costs. Build systems for training, deploying, and monitoring models. Scale our ML training infrastructure with TensorFlow and JAX. Optimize model architectures for high-throughput, low-latency environments, ensuring the ML models never compromise core Search performance. Drive model performance by testing and ingesting novel signals (including multi-modal embeddings and Large Language Model (LLM)-generated user profiles), designing and executing A/B tests to measure ML-driven feature effectiveness, and iterating quickly based on findings. Build the engine that manages and generates hyper-personalized, multi-turn LLM prompts within the new AI Mode infrastructure.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

Google's engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at a massive scale. You'll be at the forefront of innovation, developing systems and AI and Machine Learning solutions.

As a PhD graduate, your research expertise is invaluable to us. Explore a variety of projects, collaborate with various teams, and contribute to products that are changing the world, across many product areas, including AI & Infrastructure, Cloud, YouTube, Search, Ads and more!

Our engineering teams include thousands of PhDs who bring their deep knowledge and research experience to enhance our systems and products. As a Google PhD Software Engineer, you will work on critical projects, with many opportunities to learn and follow your interests. We expect our engineers to be creative and versatile, leading and identifying new problems to push the field and Google technology forward.

Google offers you exciting opportunities as it is one of the world’s leading producers and consumers of ML and AI technology, with decades of experience in designing, deploying, and using ML software and custom ML hardware infrastructure at massive scale.

The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

Collaborate or lead on team projects to carry out design, analysis, and development of advanced ML systems across the stack using your research expertise. Support building end-to-end ML Systems that involves working across the full stack, from low-level hardware acceleration and compiler optimizations to high-level model architecture and production APIs, transforming your research expertise into robust, scalable products. Optimize complex system performance by analyzing and fixing performance bottlenecks, memory inefficiencies, and errors in production systems to meet stringent customer goals. Elevate engineering excellence by writing well-tested code, conducting code reviews and fostering a culture of quality by advocating best engineering practices.