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systems engineer

Apple

<div>The Siri organization is looking for passionate Machine Learning Systems Engineers to join us in developing and shipping state-of-the-art generative AI technology to advance Siri and Apple Intelligence for Apple&rsquo;s customers. Siri is being elevated by the huge opportunities that AI brings. 
 
The organization is responsible for training on-device &amp; cloud models, evaluating various approaches, pushing the envelope with the latest generative AI research developments, and ultimately delivering product critical models that power Siri and Apple Intelligence experiences. These models ship across a wide range of products at Apple, including iPhone, Mac, Apple Watch and more, enabling millions of people around the world to get things done every day. Our team provides an opportunity to be part of an incredible research and engineering organization at Apple. By joining the team, you will work with highly talented machine learning researchers and engineers, and work on meaningful, challenging and novel problems. 
 
Description 
 
As a Machine Learning Systems Engineer, you will work closely with Siri modeling teams and other cross-functional teams to optimize model training and inference. You will be working across the ML stack at Apple, finding opportunities to make models performant, train quicker, and run faster on Apple's custom Apple Silicon. You will be joining a team that spans data, modeling, evaluation, deployment and working with engineers across ML infrastructure, inference, and framework teams. You will write production-level code to train and deploy models that will impact Apple's customers and enrich their lives. You are an ideal candidate if you: 
Are not afraid of CUDA OOM or NCCL errors 
<ul><li>
</li>
Can dig deep into an ML library to understand how tiny details impact the model 
<li>
</li><li>
Can understand complex ML systems that include data, training pipeline, export, and inference engine 
 
Preferred Qualifications 
 
Collaborative with experience working in large inter-teams projects 
 
Expertise in ML and LLM optimization such as quantization, KV Cache, Speculative Decoding 
 
Familiarity with ML training methodologies such as FSDP, DDP, and other parallelism 
 
Experience in an LLM training/eval library such as HuggingFace transformers, lm evaluation harness, Megatron-LM. 
 
Experience in optimizing LLM models and deploying LLM models 
 
Proficiency in a compiled programming language (e.g. Swift, C/C++, Java) 
 
Minimum Qualifications 
 
Experience in model lifecycle of training, evaluation, and deployment of models 
 
Strong understanding of Machine Learning (ML) model architectures (e.g. Transformers, CNN) and ML training loop 
 
Strong proficiency in Python and ML framework such as PyTorch 
 
Bachelor's degree in Computer Science, Engineering, or related discipline, or equivalent industry/project experience 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.</li></ul></div>

Machine Learning Systems Engineer

DigitalOcean

<div><div>Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you'll find your place here. We value winning together&mdash;while learning, having fun, and making a profound difference for the dreamers and builders in the world.</div><h2 class="jobSectionHeader">
We want people who are passionate about optimizing and troubleshooting data center hardware at mega-scale so our customers don't have to worry!</h2>

Reporting to the Manager of Infra Machines Design, you will act as the team lead for sustaining engineering efforts for the hardware infrastructure of the DigitalOcean server fleet. The ideal candidate will be eager to face new challenges as DigitalOcean continues to scale its data center footprint and infrastructure cloud capacity and explore new technologies and capabilities to bring to our customers, providing top-tier support for our hardware and firmware in the DO fleet.
<h2 class="jobSectionHeader">
What You'll Be Doing:</h2>
<ul><li>Act as technical lead for the Sustaining Engineering team in the Infra::Machines::Design Organization</li>
<li>Support server hardware, cabling, and networking hardware throughout its operational lifecycle Monitor the #machines channel and MACHINES JIRA project for issues and drive them to resolution</li>
<li>Participate in 24/7 on-call rotation with other members of the team</li>
<li>Act as Tier 2 escalation for Datacenter Operations (DCOPS) and Cloud Operations (CloudOps) regarding hardware and firmware components</li>
<li>Develop and maintain standards and practices for DigitalOcean hardware operations</li>
<li>Work closely with the Qualification team, Firmware team, Fleet Lifecycle Engineering team (FLE), Foresight team, and Infrastructure Services team to resolve issues in tooling, firmware packages, hardware components, and other operational concerns</li>
<li>Liase with DCOPS teams to develop, deliver, and support hardware-related runbooks</li>
<li>Liase with vendor support teams regarding hardware and firmware issues and drive issues to resolution Identify gaps in tooling and operational processes and engage appropriate peer teams to close gaps</li>
<li>Help with development of tooling and associated runbooks to address gaps in operational capabilities around hardware and firmware operationsCoordinate with Ops teams on monitoring thresholds, failure modes and alerting</li>
<li>Assist in troubleshooting cause of failures and work to prevent them in the future Raise the quality bar in the delivery of our cloud infrastructure by identifying industry best practices and working to adopt them</li>
</ul><h2 class="jobSectionHeader">What We'll Expect From You:</h2>
<ul><li>Technical Degree (BS Computer Science/Engineering) or equivalent practical experience</li>
<li>Hands-on experience operating a cloud infrastructure at mid-tier scale or better</li>
<li>An in-depth understanding of server hardware, firmware, and infrastructure</li>
<li>Strong knowledge in troubleshooting techniques, Python and BASHExtra points for JTAG debugging / Firmware troubleshooting / Wire sniffing experience</li>
<li>Clear communication and collaboration across key stakeholders An insatiable passion for constant improvement</li>
</ul><h2 class="jobSectionHeader">Compensation Range:</h2>
<ul><li>$107,000 - $134,000</li>
</ul>
<ul><li>This is a remote role</li></ul>

JR: 2026-7601

#LI-Remote<div><h2 class="jobSectionHeader">
Why You'll Like Working for DigitalOcean</h2>
<ul><li>We innovate with purpose. You'll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions.</li>
<li>We prioritize career development. At DO, you'll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.</li>
<li>We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences.</li>
<li>We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.</li>
<li>DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.</li>
</ul>
Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.</div></div>

Systems Engineer II

Motional

<div>Mission Summary: 
 
We are looking for a Machine Learning Systems Engineer to join our ML Acceleration team. In this role, you will be responsible for the core systems that enable our researchers to train frontier models at scale, focusing obsessively on speed, cost, reliability, and throughput. You will work at the intersection of machine learning research and high-performance systems engineering. Your work will directly impact our ability to scale large-scale distributed model training and reduce the time-to-convergence for our next generation of models. 

What you'll be doing:
<ul>
<li>Performance Profiling &amp; Optimization: Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading, gradient computation, and communication. Implement optimizations like kernel fusion, sharding, and tiling to improve step time.</li>
<li>Distributed Training: Optimize distributed training pipelines using frameworks such as PyTorch Distributed.</li>
<li>Kernel Development: Design and maintain high-performance GPU kernels in Triton or CUDA for state-of-the-art ML workloads.</li>
<li>Data Pipeline Engineering: Optimize robust data loading pipelines that maximize training throughput.</li> 
</ul>
What we're looking for:
<ul>
<li>Education: Bachelor's, Master's degree, or PhD in Computer Science, Computer Engineering, or a related technical discipline.</li>
<li>Software Engineering: Strong proficiency in Python.</li>
<li>ML Frameworks: Extensive hands-on experience with PyTorch.</li>
<li>ML Knowledge: Experience optimizing machine learning model execution during training and inference, alongside a strong understanding of fundamental machine learning concepts, architectures, and processes.</li>
<li>Problem Solving: Exceptional analytical and problem-solving skills, with a bias for action and a data-driven approach to technical challenges.</li> 
</ul>
We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.<div> 
Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We're driven by something more.

Our journey is always people first.

We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move.

Higher purpose, greater impact.

We're creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it's not only good for our business, it's the right thing to do.
Scale up, not starting up.

Our team is behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest-standing public robotaxi fleet. We're driven to scale; we're moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges.

Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit www.Motional.com and follow us on Twitter, LinkedIn, Instagram and YouTube.

Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.</div></div>

ML Systems Engineer, ML Acceleration

Domu

<div>
 At Domu.ai, we're building the infrastructure that will replace call centers at the world's largest financial institutions. Voice AI that handles thousands of live calls every day for Fortune 500 banks and insurers, end-to-end. Call volume is 3x-ing monthly. We're hitting problems most startups never see: real-time voice AI at scale, legacy banking infrastructure, enterprise telephony, and regulatory constraints.
 
 
 The role
 
 
 \ As the
 
 Software Engineer
 
 you'll.....
 
 
 <ul>
 <li>
 Build and own core product features: Backend systems, APIs, voice infrastructure, wherever the product needs you. Code ships daily and goes live for Fortune 500 clients.
 </li>
 <li>
 Work on things most engineers never touch: telephony systems, real-time voice processing, and integrations with legacy financial infrastructure. The problems are hard. That's the point.
 </li>
 <li>
 95%+ of your time will be coding and building.
 </li>
 <li>
 We're looking for engineers who can own one of these areas: the orchestration layer that coordinates our voice AI systems, infrastructure scaling and low-level performance, security as a generalist building for Fortune 500 financial institutions, or product engineering close to users finding high-leverage wins.
 </li>
 <li>
 Know what it feels like when things are working: real customers, real revenue, a product people actually need. You also know the chaos, the pace, the things that break at the worst possible time. You've seen both sides and you want to do it again with a team that's already found traction.
 
 
 </li>
 </ul>
 How we work
 
 
 <ul>
 <li>
 Four engineers. Everyone ships to production.
 </li>
 <li>
 We do dailies. We groom tickets. But we keep process light and in service of the work, not the other way around. We'd rather spend time building than talking about building.
 </li>
 <li>
 We care about doing great work. Not just shipping, but shipping something you're proud of. Clean abstractions. Systems that don't page you at 3am. Code you wouldn't be embarrassed to open-source. We build things that last because we're the ones maintaining them.
 </li>
 <li>
 Ownership here is real. You won't be handed tasks from a backlog. You'll see what needs to happen and do it. That's how a small team ships to Fortune 500 customers.
 </li>
 <li>
 We hire people whose judgment we trust, then get out of their way. No passengers.
 
 
 </li>
 </ul>
 What you bring
 
 
 <ul>
 <li>
 3+ years of experience as a software engineer
 </li>
 <li>
 Previously worked at a Series A (or similar stage) startup and went through the same hypergrowth challenges Domu is facing
 </li>
 <li>
 Experience dealing with legacy systems and refactoring them into sustainable, scalable architectures
 </li>
 <li>
 Strong backend fundamentals - can own features end-to-end from design to production
 </li>
 <li>
 Proficiency in TypeScript and/or Python
 </li>
 <li>
 Cares about doing great work - clean abstractions, reliable systems, code you'd be proud to open-source
 
 
 </li>
 </ul>
 Extras we'd be excited about
 
 
 <ul>
 <li>
 Telephony/Voice infrastructure - SIP, SRTP, WebRTC, or platforms like Telnyx, Twilio, LiveKit
 </li>
 <li>
 High-throughput distributed systems - queue workers, event-driven architectures, handling 1M+ daily transactions
 </li>
 <li>
 PostgreSQL at scale - query optimization, replication, connection pooling
 </li>
 <li>
 Kubernetes - production deployments, scaling stateful services
 </li>
 <li>
 Real-time data pipelines - ClickHouse, Kafka, or similar OLAP/streaming solutions
 </li>
 <li>
 AWS infrastructure - SQS, containerized deployments
 </li>
 <li>
 Compliance-conscious environments - SOC 2, ISO 27001, or fintech/enterprise security requirements
 </li>
 <li>
 Experience with AI/ML integrations in production (LLMs, voice AI)
 </li>
 <li>
 Familiarity with contact center / dialer systems
 </li>
 <li>
 You've been through the early stages of a startup before.
 </li>
 <li>
 You care about the craft. You want to build something good, not just something that works.
 
 
 </li>
 </ul>
 Why Domu
 
 
 <ul>
 <li>
 You'll be engineer #5. Small team, high leverage. Your work ships immediately.
 </li>
 <li>
 Real traction. Post-revenue, Fortune 500 customers, 3x monthly growth. This isn't a bet on an idea. The product works and customers are paying for it.
 </li>
 <li>
 You'll learn how enterprise deals work from an engineering seat. You'll see the direct line between your code and revenue.
 </li>
 <li>
 Early enough to shape the product, the team, and the culture.
 
 
 </li>
 </ul>
 What we offer
 
 
 <ul>
 <li>
 Healthcare
 </li>
 <li>
 weekly stipend for food and transportation
 </li>
 <li>
 gym membership
 </li>
 <li>
 equipment budget (strict rules on noisy mechanical keyboards)
 </li>
 <li>
 whatever tools you need
 </li>
 </ul>
</div>

Software Engineer

Acceler8 Talent

<div>
 
 🚨
 
 Hiring: Machine Learning Engineer (Optimization / Decision Systems)
 
 
 
 📍 San Francisco (Onsite)
 
 
 💰 Up to $250K + Equity (Dependent on experience)
 
 
 
 
 
 Most companies still manage digital advertising like it&rsquo;s 2015. Manually adjusting budgets, guessing which campaigns work, and relying on black-box metrics from ad platforms.
 
 
 We&rsquo;re working with a venture-backed startup building something very different:
 
 
 An AI-driven optimization engine that autonomously allocates advertising spend using the same quantitative rigor used in high-frequency trading and financial markets.
 
 
 Instead of humans manually managing campaigns, their system continuously decides:
 
 
 &bull; Where budget should go
 
 
 &bull; When bids should change
 
 
 &bull; Which creative is losing performance
 
 
 &bull; How to maximize return across platforms
 
 
 
 
 
 
 What You&rsquo;ll Work On:
 
 
 
 🧠 Build models for LTV prediction and budget optimization
 
 
 ⚙️ Design risk-aware algorithms that control how millions in ad spend is deployed
 
 
 🔌 Build real-time integrations with platforms like Meta, Google &amp; TikTok
 
 
 📊 Develop simulation &amp; backtesting systems before strategies go live
 
 
 🚀 Take models from research &rarr; production &rarr; monitoring
 
 
 
 
 
 
 Ideal Background:
 
 
 
 ✔️ 4+ years in Machine Learning or Applied ML Engineering
 
 
 ✔️ Strong foundation in statistics, probability, and optimization
 
 
 ✔️ Experience deploying ML models in production systems
 
 
 ✔️ Builders who care about real-world impact, not just research
 
 
 
 
 
 ⭐ Bonus if you&rsquo;ve worked in quant finance, algorithmic trading, or adtech
 
 
 
 
 
 
 Why This Role Is Interesting:
 
 
 
 &bull; You&rsquo;ll build systems that control real-world financial decisions
 
 
 &bull; Early engineer helping shape the core architecture
 
 
 &bull; Opportunity to work on a $1T+ global market
 
 
 &bull; Meaningful equity at an early stage
 
 
 
 
 
 If you're interested or know someone who might be, DM me or apply below 👇👇
 
</div>

Machine Learning Engineer

Uber

<div>
 
 About The Role
 
 
 
 Uber is looking for a Software Engineer to join our Matching Platform team. This team sits at the core of Uber's real-time marketplace, ensuring that riders and drivers are matched efficiently, fairly, and at scale.
 
 
 Matching is one of Uber's most complex and impactful engineering problems, requiring expertise in high-scale distributed systems, real-time decision-making, and machine learning infrastructure. As a Senior Engineer, you'll play a key role in evolving our matching architecture, improving system efficiency, and enabling Uber's next-generation ML-powered matching capabilities. This is an opportunity to work on one of Uber's most business-critical domains with massive global impact.
 
 
 
 Some Of The Problems You'll Be Working On Include
 
 
 
 <ul>
 <li>
 Building a highly scalable matching platform - handling millions of ride requests per second with ultra-low latency.
 </li>
 <li>
 Designing extensible architectures - creating a modular and flexible platform that allows new product innovations without complex rewrites.
 </li>
 <li>
 Evolving the ML platform for matching - enabling real-time inference, model deployment, and experimentation at scale.
 
 
 </li>
 </ul>
 
 What The Candidate Will Do
 
 
 
 <ul>
 <li>
 Build and scale a low-latency platform powering millions of real-time match decisions per second
 </li>
 <li>
 Design modular systems that accelerate product innovation without rework
 </li>
 <li>
 Optimize for fairness, efficiency, and marketplace health at global scale
 </li>
 <li>
 Collaborate across product, infra, and ML teams to deliver business-critical impact
 
 
 </li>
 </ul>
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics or related field OR 3-year full-time Software Engineering work experience, WHICH INCLUDES 3-year total technical software engineering experience in one or more of the following areas:
 </li>
 <li>
 Programming language (e.g. C, C++, Java, Python, or Go)
 </li>
 <li>
 Note the 3-year total of specialized software engineering experience may have been gained through education and full-time work experience, additional training, coursework, research, or similar (OR some combination of these). The year of specialized experience is not necessarily in addition to the years of Education &amp; full-time work experience indicated.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 3+ years of technical software engineering experience in one or more of the following areas:
 </li>
 <li>
 Experience with distributed systems or microservice architectures.
 </li>
 <li>
 Experience with relational databases and distributed storage systems (MySQL, Cassandra).
 </li>
 <li>
 Passion for learning new technologies
 </li>
 <li>
 Experience with shipping efficient, reliable, crash-free code that reaches millions of users.
 
 
 </li>
 </ul>
 For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits., For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.
</div>

Software Engineer II, Matching Platform

Together AI

<div>
 
 About The Role
 
 
 
 Together AI is seeking a Machine Learning Engineer to join our Inference Engine team, focusing on optimizing and enhancing the performance of our AI inference systems. This role involves working with state-of-the-art large language models models and ensuring they run efficiently and effectively at scale. If you are passionate about AI inference, PyTorch, and developing high-performance systems, we want to hear from you. This position offers the chance to collaborate closely with AI researchers and engineers to create cutting-edge AI solutions. Join us in shaping the future at Together AI!
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design and build the production systems that power the Together AI inference engine, enabling reliability and performance at scale.
 </li>
 <li>
 Develop and optimize runtime inference services for large-scale AI applications.
 </li>
 <li>
 Collaborate with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world.
 </li>
 <li>
 Conduct design and code reviews to ensure high standards of quality.
 </li>
 <li>
 Create services, tools, and developer documentation to support the inference engine.
 </li>
 <li>
 Implement robust and fault-tolerant systems for data ingestion and processing.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 3+ years of experience writing high-performance, well-tested, production-quality code.
 </li>
 <li>
 Proficiency with Python and PyTorch.
 </li>
 <li>
 Demonstrated experience in building high performance libraries and tooling.
 </li>
 <li>
 Excellent understanding of low-level operating systems concepts including multi-threading, memory management, networking, storage, performance, and scale.
 </li>
 <li>
 Preferred: Knowledge of existing AI inference systems such as TGI, vLLM, TensorRT-LLM, Optimum
 </li>
 <li>
 Preferred: Knowledge of AI inference techniques such as speculative decoding.
 </li>
 <li>
 Preferred: Knowledge of CUDA/Triton programming.
 </li>
 <li>
 Nice to have: Knowledge of Rust, Cython and compilers.
 
 
 </li>
 </ul>
 
 About Together AI
 
 
 
 Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society. Together, we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI. Our team has been behind technological advancements such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey to build the next-generation AI infrastructure.
 
 
 
 Compensation
 
 
 
 We offer competitive compensation, startup equity, health insurance, and other competitive benefits. The US base salary range for this full-time position is $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level, and role. Individual compensation will be determined by experience, skills, and job-related knowledge.
 
 
 
 Equal Opportunity
 
 
 
 Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunities to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.
 
 
 Please see our privacy policy at https://www.together.ai/privacy
</div>

Machine Learning Engineer - Inference

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