Explore 3 open source program developer jobs from 3 hiring companies in Newman, CA, US. Filter by remote, salary, experience, and company, then open any listing to apply.

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Open Source Program Developer Jobs

Lawrence Livermore National Laboratory

Nutanix

Hybrid

WHAT YOU DO AT AMD CHANGES EVERYTHING At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond.  Together, we advance your career.   <h2>THE ROLE: </h2><div class="scriptor-paragraph">Triton is a widely adopted language and compiler for high-performance GPU kernels, powering major AI frameworks such as PyTorch, vLLM, and SGLang. As AI workloads increasingly rely on Triton-based kernels, first-class Triton support is strategically critical to AMD’s AI software roadmap.</div><div class="scriptor-paragraph"> </div><div class="scriptor-paragraph">AMD GPUs are an official Triton backend; delivering industry-leading Triton performance on AMD Instinct accelerators is a top priority for AMD. The performance and usability of Triton directly impact the competitiveness of AMD hardware in large-scale AI training and inference.</div><div class="scriptor-paragraph">In this role you will author state-of-the-art performant Triton/Gluon kernels for ML kernels powering the latest and greatest AI models.</div><div class="scriptor-paragraph"> </div><div class="scriptor-paragraph">You will collaborate with research, compiler, and hardware architecture teams to co-design high-performance solutions, analyze bottlenecks to make AMD GPUs the best-in-class platform for Triton-powered AI workloads.</div><h2>THE PERSON: </h2><div class="scriptor-paragraph">The ideal candidate has deep expertise in SIMT programming, parallel algorithms, GPU architecture, and performance engineering. You are comfortable working across the full stack to drive e2e model performance — from vLLM/SGL down to ISA-level performance tuning — and can perform rigorous quantitative analysis to drive measurable improvements.</div><div class="scriptor-paragraph"> </div><div class="scriptor-paragraph">You thrive in highly technical environments, enjoy solving complex performance problems, and are excited to collaborate across model deployment, compiler, runtime, and hardware teams. Most importantly, you are curious, hands-on, and willing to learn and work across boundaries.</div><h2>KEY RESPONSIBILITIES:</h2><ul class=""><li class="scriptor-listItemlist!list-3dfaacd1-b1c8-42cd-8dc2-660993d1370a0">Design, research, implement, and rigorously optimize high-performance matmul, attention (flash, paged, grouped-query), MoE, and fully fused transformer kernels using Triton, targeting large-scale LLM and multimodal workloads</li><li class="scriptor-listItemlist!list-3dfaacd1-b1c8-42cd-8dc2-660993d1370a0">Own and productionize critical Triton/Gluon kernels within vLLM and SGL (e.g., paged attention, extend attention, MoE, quantized kernels, etc), ensuring correctness, scalability, and peak throughput </li><li class="scriptor-listItemlist!list-3dfaacd1-b1c8-42cd-8dc2-660993d1370a0">Partner closely with compiler engineers to develop and maintain the Triton AMD backend across ROCm and the LLVM AMDGPU stack, targeting CDNA and next-generation architectures </li><li class="scriptor-listItemlist!list-3dfaacd1-b1c8-42cd-8dc2-660993d1370a0">Drive deep kernel-level optimizations across the AMD memory hierarchy (LDS, L2, HBM), wavefront execution (wave32/wave64), vectorization, MFMA utilization, occupancy tuning, and instruction scheduling to maximize hardware efficiency </li><li class="scriptor-listItemlist!list-3dfaacd1-b1c8-42cd-8dc2-660993d1370a0">Perform rigorous profiling and microbenchmarking led optimization on AMD Instinct GPUs using hardware counters and tracing tools; root-cause bottlenecks in memory bandwidth, latency hiding, synchronization, and register pressure </li><li class="scriptor-listItemlist!list-3dfaacd1-b1c8-42cd-8dc2-660993d1370a0">Debug and resolve performance and correctness issues end-to-end across PyTorch, vLLM/SGL runtimes, Triton IR/MLIR, ROCm runtime, and the LLVM AMDGPU backend </li><li class="scriptor-listItemlist!list-3dfaacd1-b1c8-42cd-8dc2-660993d1370a0">Collaborate closely with GPU architecture and performance teams to co-design performance-critical features </li><li class="scriptor-listItemlist!list-3dfaacd1-b1c8-42cd-8dc2-660993d1370a0">Contribute to open-source Triton, LLVM, and ROCm ecosystems</li></ul><h2>PREFERRED EXPERIENCE: </h2><ul class=""><li class="scriptor-listItemlist!list-3dfaacd1-b1c8-42cd-8dc2-660993d1370a1">5+ years of experience in GPU kernel development, compiler backends, or performance engineering focused on AI/ML workloads </li><li class="scriptor-listItemlist!list-3dfaacd1-b1c8-42cd-8dc2-660993d1370a1">Strong hands-on expertise with Triton, including writing custom matmul, attention, and fused transformer kernels and understanding Triton IR lowering to GPU backends </li><li class="scriptor-listItemlist!list-3dfaacd1-b1c8-42cd-8dc2-660993d1370a1">Deep understanding of modern GPU architectures (wavefront execution, memory hierarchy, scheduling, occupancy) </li><li class="scriptor-listItemlist!list-3dfaacd1-b1c8-42cd-8dc2-660993d1370a1">Meaningful contributions to open-source projects such as Triton, Torch, vLLM, SGLang, IREE, MLIR, LLVM, or ROCm, with a strong collaborative and upstream-first engineering mindset </li><li class="scriptor-listItemlist!list-3dfaacd1-b1c8-42cd-8dc2-660993d1370a1">Proven ability to mentor junior engineers and drive kernel optimization efforts in a fast-paced, research-driven environment</li></ul><h2>PREFERRED ACADEMIC CREDENTIALS: </h2><div class="scriptor-paragraph">    Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.</div><div class="scriptor-paragraph"> </div>This role is not eligible for visa sponsorship.  #LI-G11 #LI-HYBRID Benefits offered are described:  <a href="https://www.amd.com/en/corporate/careers/benefits.html" target="_blank" rel="noopener">AMD benefits at a glance</a>. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law.   We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. AMD may use Artificial Intelligence to help screen, assess or select applicants for this position.  AMD’s “Responsible AI Policy” is available <a href="https://www.amd.com/en/legal/responsible-ai-use-policy.html" target="_blank" rel="noopener">here.</a> This posting is for an existing vacancy.

Senior Software Engineer - AI Triton Kernels

Senior Software Engineer

GPU kernel development and Triton expertise; 5+ years; strong C/C++/GPU programming; open-source contributions.

Engineering
 
 San Jose,
 California
 

 Req.Num.: 31165

Hungry, Humble, Honest, with Heart. The OpportunityNutanix is a global leader in cloud software and Hyperconverged infrastructure solutions, making infrastructure invisible so that IT can focus on the applications and services that power their business. Companies around the world use Nutanix Enterprise Cloud OS software to bring one-click application management and mobility across public, private and distributed edge clouds so they can run any application at any scale with a dramatically lower total cost of ownership. The result is organizations that can rapidly deliver a high-performance IT environment on demand, giving application owners a true cloud-like experience. About the TeamAt Nutanix, you will be part of the Data Platform team – engineers  working across India and the US team and passionate about open source and distributed data infrastructure. We build and operate internal platforms around ClickHouse (analytical database) and NATS (streaming service) that power analytics and real-time workloads across 10+ Nutanix products. Product teams depend on us for reliable, scalable, and performant data solutions — and we take pride in being the subject matter experts (SMEs) for ClickHouse and NATS within Nutanix. We love open source, have actively contributed over 50 patches upstream, maintain internal forks wherever required and bring the best of the OSS world into our ecosystem.  The team culture emphasizes unity, deep engineering, a shared focus on achieving goals, fostering collaboration and innovation. Working closely together, team members value each other's contributions and support one another in a dynamic and fast-paced environment. You will report to a Staff Engineer at Nutanix. The work setup is hybrid, allowing for flexibility and a healthy work-life balance. As a new hire, you will be expected to work from the office three days a week, ensuring face-to-face interactions with your team members and promoting a sense of camaraderie and community within the Data Platform team. At Nutanix, we understand the importance of work-life balance and prioritize the well-being of our employees. Therefore, there are no travel requirements for this position, allowing you to focus on your work and professional development without the added stress of frequent travel. Your Role<ul><li>Design, build, and maintain scalable distributed data systems using ClickHouse and NATS.</li><li>Write high-quality, efficient, and maintainable code for core data platform components.</li><li>Participate in ClickHouse and NATS open-source communities — stay current with updates, usage patterns, and contribute wherever required.</li><li>Debug and optimize distributed systems in production to ensure performance and reliability.</li><li>Evaluate emerging technologies and open-source tools that can strengthen the platform and drive adoption across teams.</li><li>Build and operate robust internal platforms that power multiple engineering teams within Nutanix.</li></ul> What You Will Bring<ul><li>Bachelor’s or Master’s degree in Computer Science or a related field.</li><li>Passion for programming with strong expertise in one or more languages — C++ or Go preferred.</li><li>Solid foundation in data structures and algorithms.</li><li>Deep understanding of operating system internals, networking, and distributed systems concepts.</li><li>Experience designing and building high-performance, fault-tolerant, and scalable distributed data systems atop Kubernetes.</li><li>Familiarity with analytical databases (e.g., ClickHouse, Druid) or streaming systems (e.g., NATS, Kafka, Pulsar).</li><li>Proven ability to work with large, complex codebases and deliver high-quality, maintainable software.</li><li>Strong grasp of design patterns and the ability to evaluate trade-offs when applying them.</li><li>Prior open-source contributions, especially to distributed databases or data infrastructure projects, are a strong plus.</li></ul> Work ArrangementHybrid: This role operates in a hybrid capacity, blending the benefits of remote work with the advantages of in-person collaboration. In locations where our workplace policy applies (i.e. San Jose, Durham, Mexico City, Bangalore, Pune, Hoofddorp, Belgrade, Barcelona, Singapore, Sydney and Tokyo), employees are expected to work onsite a minimum of 3 days per week to foster collaboration, team alignment, and access to in-office resources. Workplace type may vary based on location and team requirements. Please speak with your recruiter for details. Additional team-specific guidance and norms will be provided by your manager. The pay range for this position at commencement of employment is expected to be between USD $ 143,200 and USD $ 285,598 per year.However, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements, including a sign-on bonus, restricted stock units, and discretionary awards in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave), dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.If hired, employee will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors. Our application deadline is 40 days from the date of posting. In good faith, the posting may be removed prior to this date if the position is filled or extended in good faith. 
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Member of Technical Staff 3 (CPaaS Data Platform Team)

Member of Technical Staff

Bachelor’s or Master’s in Computer Science or related field; strong programming skills in C++ or Go; knowledge of data structures, algorithms, OS internals, networking, distributed systems; experience with Kubernetes, analytical databases or streaming systems; open-source contributions a plus.

Company Description:Join us and make YOUR mark on the World!Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.&#xa0;Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.Job Description:We&#xa0;have an opening for a Postdoctoral Researcher in Operations Research to conduct research in the areas of stochastic, decentralized, and/or multi-level optimization, with specific application to critical infrastructure systems. You will be an integral part of a multi-disciplinary team of researchers, with skill sets ranging from computer and climate science to power and industrial engineering; projects are typically collaborative with partner academic institutions and other national labs. You will be developing advanced models of decision-making under uncertainty and adversarial contexts for critical infrastructure operations, planning, and resilience. You will join ongoing efforts in strategic capacity expansion planning and infrastructure interdiction but may also support other research initiatives sponsored by our U.S. Government partners.&#xa0; You will work with experienced LLNL scientists and engineers and contribute to new numerical methods and analysis tools that provide insights to inform near and long-term strategy and technology decisions. This position is in the Computational Engineering Division (CED), within the Engineering Directorate. The research will be conducted in conjunction with LLNL’s Cyber and Infrastructure Resilience (CIR) program.Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week.In this role, you will<ul><li>Develop and extend mathematical programming (e.g., mixed-integer programming, nonlinear programming, and mixed-integer nonlinear programming) formulations of core critical infrastructure operations and planning optimization models.&#xa0;</li><li>Design and implement high-performance (parallel) solvers for stochastic, multi-level, and/or decentralized optimization models of critical infrastructure.</li><li>Analyze and mitigate performance bottlenecks in parallel solver implementations.</li><li>Publish research results in external peer-reviewed scientific journals and participate in conferences and workshops.</li><li>Contribute to grant proposals and collaborate with others in a multidisciplinary team environment to accomplish research goals.</li><li>Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internal and external to the Laboratory.</li><li>Perform other duties as assigned.</li></ul>Qualifications:<ul><li>Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.</li><li>Ph.D. in Operations Research, Industrial Engineering, Computer Science, Applied Mathematics, or closely related field.</li><li>Fundamental knowledge of at least one open-source algebraic modeling language (e.g., Pyomo, JuMP) for mathematical optimization.</li><li>Fundamental knowledge of at least one widely used mathematical optimization solver (e.g., HiGHS, Ipopt, Gurobi, CPLEX, and Xpress).</li><li>Fundamental knowledge and experience developing software in a high-level language such as Python, Julia, and C++ (Python preferred).</li><li>Experience developing specialized algorithms for mathematical optimization problems considering either adversarial (multi-level) behaviors, uncertain inputs, or at a large scale.</li><li>Publication record in high-quality peer-reviewed journals and/or conferences.</li><li>Proficient verbal and written communication skills to effectively collaborate in a team environment, present and explain technical information to technical as well as non-technical audiences, document work and write research papers.</li></ul>Qualifications We Desire<ul><li>Experience with high-performance computing systems, specifically parallel programming libraries such as MPI.</li><li>Experience with the application of mathematical optimization to critical infrastructure systems, including electricity grid and natural gas networks.</li><li>Experience processing and analyzing critical infrastructure information.</li></ul>Pay Range$122,028 - $143,328 AnnuallyThis is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage.&#xa0;An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.Additional Information:#LI-Hybrid<div sr-tagline=""></div>Position InformationThis is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.
Why Lawrence Livermore National Laboratory?<ul><li>Included in 2026&#xa0;Best Places to Work by Glassdoor!</li><li>Flexible&#xa0;<a href="https://www.llnl.gov/join-our-team/culture/benefits">Benefits Package</a></li><li>401(k)</li><li>Relocation Assistance</li><li>Education Reimbursement Program</li><li>Flexible schedules (*depending on project needs)</li><li>Our values - visit&#xa0;<a href="https://www.llnl.gov/diversity/our-values">https://www.llnl.gov/inclusion/our-values</a></li></ul>
Security ClearanceThis position requires a Department of Energy (DOE) Q-level clearance.&#xa0;&#xa0;If you are selected, we&#xa0;will initiate a Federal background investigation to determine if you&#xa0;meet eligibility requirements for access to classified information or matter. Also, all L or Q cleared employees are subject to random drug testing.&#xa0; Q-level clearance requires U.S. citizenship.&#xa0;
Pre-Employment Drug TestExternal applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.
Wireless and Medical DevicesPer the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use&#xa0;and/or possession of&#xa0;mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where&#xa0;you are not permitted to have a personal and/or laboratory mobile device&#xa0;in your possession.&#xa0; This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.&#xa0;&#xa0;If&#xa0;you use&#xa0;a&#xa0;medical device, which&#xa0;pairs with a mobile device,&#xa0;you must still follow the rules concerning&#xa0;the mobile device in individual sections within Limited Areas.&#xa0; Sensitive Compartmented Information Facilities require&#xa0;separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.
How to identify fake job advertisementsPlease be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.To learn more about recruitment scams:&#xa0;<a href="https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf">https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf</a>
Equal Employment OpportunityWe are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.Reasonable AccommodationOur goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory.&#xa0; If you need a reasonable accommodation during the application or the recruiting process, please use our <a href="https://www.llnl.gov/join-our-team/careers/accessibility">online form</a> to submit a request.&#xa0;
California&#xa0;Privacy NoticeThe California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles&#xa0;job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed <a href="https://www.llnl.gov/join-our-team/careers/privacy-statement">here</a>.

Operations Research Postdoctoral Researcher

PhD in Operations Research, Industrial Engineering, Computer Science, Applied Mathematics; DOE Q-level clearance (or eligibility); strong optimization knowledge; programming in Python/Julia/C++; experience with open-source modeling languages and solvers; publication record; good communication and collaboration skills.

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