Software Engineer Ml Infrastructure Jobs

About Ema Ema builds AI Employees for HR, IT and Finance. Our AI Employees take on the busy work across the employee experience, from recruiting, onboarding and benefits to IT support, invoice processing and payroll, so people can spend their time on work that needs them. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Creaegis, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production. We ship real systems that run real business processes at scale. Build agents that learn from the work they do. Ema builds AI employees that carry out complex workflows across enterprise applications. Our ML team works on the loop that makes them better: production traces become data, data becomes training and evaluation, and better agents produce better traces. The hard part is deciding which intervention will improve behavior in the next real workflow. The problem space Harnesses and inference-time compute. Design context, tools, skills and orchestration for multi-step agents, including work across documents, slides, images, audio and video. Test where extra reasoning, search or verification earns its latency and cost. Build self-improvement loops with explicit permissions, evaluation gates and rollback. Agent post-training. Curate trajectories for SFT, optimize preferences, or run RL on real agent tasks. Investigate methods such as DPO, GRPO or DAPO where they fit; compare process and outcome supervision, shape rewards, and distill useful frontier behavior into smaller models. Measure whether gains transfer beyond the training environment. Environments and rewards. Turn enterprise workflows into reproducible training

Zoox made the world’s first purpose-built commercial robotaxi, combining advanced self-driving hardware and software. In order to ensure safe operation, low latency and consistent resource utilization are critical. The Planner Compute team is responsible for the performance of the largest single software component within the autonomy stack, the motion planner. The Planner Compute team is looking for an expert in GPU performance. You will instrument, monitor, analyze and optimize GPU-based algorithms that are performance-critical for our solution. The scope for GPU usage ranges from machine learning inference to custom CUDA kernels written specifically for the motion planner. In this role, you will: Analyze performance metrics to identify GPU hotspots and optimizations Contribute to the adaptation of our current planner to multiple GPU architectures with different resources Optimize ML models for latency and GPU memory usage Support engineers within Planner as a subject matter expert on CUDA & GPU performance Qualifications BS in computer science or related field and 8+ years of experience. Strong knowledge of CUDA as applied to recent GPU microarchitectures (e.g., Ampere, Blackwell) and experience debugging/optimizing GPU kernels using tools like Nsight. Strong knowledge of C++ and experience in large code bases, comfortable in Linux development environments. Experience in development, debugging, and profiling of complex multiprocess systems (e.g., robotic systems, game engines). Bonus Qualifications GPU kernel development experience There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies onl

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,500 firms in 60 countries use Addepar to manage and advise on nearly $10 trillion in assets. Its open platform integrates with 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and levels of complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, São Paulo, London, Edinburgh, Geneva, Warsaw, Dubai, Pune and Singapore. The Role Did you know? Alternative investing has the potential to generate higher returns compared to traditional investments over the long term. AI and Machine Learning are revolutionizing the way alternative investments are managed and analyzed. Investors are using these technologies to gain insights, see opportunities, and optimize their investment strategies. Addepar is building solutions to support our clients' alternatives investment strategies. The alternatives data management product is a serverless, modular and terraformed stack. We're hiring a Senior Software Engineer to design, implement and deliver modern software solutions that ingest and process ML-extracted data. You will collaborate closely with cross-functional teams including data scientists and product managers to build intuitive solutions that revolutionize how clients experience alternatives operations. You will work closely with operations engineering on document-based workflow automation and peer engineering teams to define the tech stack. You will iterate quickly through cycles of testing a new product offering on Addepar. If you've crafted scalable systems, or worked with phenomenal teams on hard problems in financial data, or are just interested in solving really

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. About the Role One of our north stars is a future where teams can hire Grok as a remote colleague. Reaching that future requires training our models in realistic, diverse environments that support complex, end-to-end work across domains. As a Software Engineer on the RL Environments team at SpaceXAI, you’ll build the systems that turn real-world data into high-quality environments and tasks for reinforcement learning. You’ll create dramatically more realistic training environments while owning the shared platforms and quality layers that help us produce trustworthy data quickly and at scale. This role sits at the intersection of research, data, and engineering. You’ll work closely with ML Platform and research teams to turn company data, Grok Bot interactions, vendor-built tasks, tutor data, acquired data, and synthetic data into training-ready environments. Your work will make high-quality RL data easier to create, validate, discover, and use across our model-training efforts. What you’ll work on Building platforms that allows us to build complex, realistic, and diverse RL environments at scale, that support end-to-end tasks across knowledge-work domains. Designing end-to-end f

About the Team The Applied team works across research, engineering, product, and design to bring OpenAI’s technology to the world. We seek to learn from deployment and broadly distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. We aim to make our innovative tools globally accessible, transcending geographic, economic, or platform barriers. Our commitment is to facilitate the use of AI to enhance lives, fostered by rigorous insights into how people use our products. About the Role We are seeking Software Engineers (Emerging Talent) to join our Applied Engineering team. You’ll work in a highly iterative, collaborative, fast-paced environment to bring our technology to millions of users around the world, and ensure it’s delivered with safety and reliability in mind. We value engineers who are self-starters, care deeply about the end user experience, and take pride in building products to solve customer needs. In this role, you will: Own the development of new customer-facing ChatGPT and OpenAI API features and product experiences end-to-end Talk to users to understand their problems and design solutions to address them Collaborate with a cross-functional team of engineers, researchers, product managers, designers, and operations folks to create cutting-edge products Optimize applications for speed and scale Create a diverse and inclusive culture that makes all feel welcome. Your background looks something like: Bachelor's or Master’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 0-1 years of experience in software engineering or a relevant field Proficiency with JavaScript, React, and some backend languages (we use Python) Some experience with relational databases like Postgres/MySQL Interest in AI/ML (direct experience not required) Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadl

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The Reddit Consumer Engineering organization builds and scales the products that Redditors use directly to discover content, participate in communities, and connect with others. Sitting at the intersection of large-scale distributed systems and core user journeys, Product Backend Engineers in Consumer Engineering partner directly with Product Managers, Designers, Data Scientists, ML Engineers, and Frontend Engineers to build, experiment with, and scale features that power how hundreds of millions of users discover, join, navigate, and engage with Reddit. This centralized role hires across several high-impact consumer teams, including: Core Product & Feeds: Home Experience, Recommendations & Content Discovery, Content Contribution Community & Presence: Reddit Pro, Youth Experience & Teen Safety, Creator Tools Growth & Engagement: Authentication, Notifications, Social Sharing, SEO, Onboarding. Monetization & Conversion: Paid User Acquisition, Conversion Funnel Optimization Identity & Security: Account Management, Trust & Safety What You’ll Do Cross-Functional Product Architecture: Partner closely with Product Management, Product Design, Data Science, and Client Engineers (iOS/Android/Web) to translate business and user needs into reliable, low-latency technical solutions. End-to-End Delivery: Own the full software lifecycle for major product initiatives from technical design docs and API contracts to development, testing, rollout, and observability. Metrics & Experimentation-Led Enginee

About Appier Appier is a software-as-a-service (SaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. About the Role Appier is seeking a Software Engineer, Ad Serving to be the deepest technical problem-solver behind our advertising products. When a campaign underdelivers, when CVR drops without an obvious cause, or when a partner integration behaves unexpectedly, you are the person who reproduces the issue, reads the logs, queries the data, and gets to the actual root cause — then explains it in language a client or an account team can act on. You will work at the intersection of ad serving, data, and machine learning: diagnosing delivery and performance issues across the full funnel from bid request to conversion, validating partner and supply integrations, and turning what you find into concrete improvements to our bidding and supply strategy. You will also build the tooling and playbooks that let the rest of the organization resolve these issues without you. [The seniority/title is determined by job-related skills, experience, and evaluation after the interview.] Responsibilities Own Tier 2/3 escalations across ad serving, tracking, data pipelines, and ML-driven bidding Perform root cause analysis on delivery failures, pacing anomalies, and performance metric fluctuations (CTR/CVR/CPA/ROAS) Debug OpenRTB integrations, VAST/video, SDKs, MMP postbacks, and conversion tracking (S2S, CAPI, SKAdNetwork) Use SQL to analyze large-scale bid/impression/conversion data and isolate anomalies Analyze supply-side data (SupplyChain object, ads.txt, sellers.json) to strengthen delivery strategy and flag invalid traffic Build internal tools and

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Your journey as a Software Engineer Working in our team you will: Think creatively to find optimal solutions to our complex, often ambiguous problems Participate in all stages of developing and serving new platforms for various AI solutions and improving existing Snowflake’s functionalities in the AI domain Work closely with other research, engineering, and business teams to understand and shape the short and long-term product development strategy Serve as a mentor to less experienced engineers, researchers, and product managers Ideal candidate 3+ years of experience writing production-quality scalable code using backend languages (preferred Go, Java, C++, Python) BSc in a technical field (AI/ML, CS, DS, Physics, Math, etc), MSc/PhD is a plus Professional level in building SDKs / web service APIs (REST/ gRPC) Experience with software engineering best practices (programming, testing, version control, CI/CD, docker/Kubernetes, Jenkins, agile development, etc) High levels of curiosity and eager enthusiasm for open-ended problems. Experience and interest in problem formulation based on relatively abstract information Ability to articulate results and complex concepts to leadership Must be able to produce solutions independently in an organized manner, work in a team, and also b

About the Team Our mission at OpenAI is to discover and enact the path to safe, beneficial AGI. To do this, we believe that many technical breakthroughs are needed in generative modeling, reinforcement learning, large-scale optimization, active learning, and other areas. The team builds the performance-critical systems that allow OpenAI's models to run efficiently across a diverse set of AI accelerators. We work across the inference stack, from low-level kernels and compilers through model execution, to unlock the full capabilities of the underlying hardware. About the Role As a Software Engineer, Trainium, you will help bring OpenAI's inference workloads to AWS Trainium and build the software stack required to run cutting-edge frontier models efficiently on the platform. This is a deeply technical, cross-stack role spanning kernels, compilers, and model execution. You will work on the systems needed to support OpenAI's inference stack on Trainium, including developing and optimizing high-performance kernels, improving compiler support, and enabling efficient execution of the model forward pass. You'll work closely with engineers across inference, compilers, kernels, and ML systems to identify performance bottlenecks and build the software needed to take full advantage of Trainium. The work may range from low-level hardware-specific optimization to compiler and runtime improvements to integrating new model architectures into the inference stack. If you enjoy working at the intersection of ML systems, compilers, kernels, and accelerator hardware, this role is for you. We're looking for engineers who are self-directed, comfortable operating across abstraction layers, and excited to solve challenging performance problems for frontier-scale AI systems. In This Role, You Will Build and optimize OpenAI's inference stack for AWS Trainium. Develop high-performance kernels for critical model operations and workloads. Extend and improve compiler support to efficiently target

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Our mission depends on having a digital representation of the physical world - a map with all routing related (real-time) information. This is what makes Lyft different from many products: our products don’t just facilitate online interactions, they facilitate dynamic, real-world ones. Without mapping services, none of these real world interactions between people and transport can happen. The Mapping organization at Lyft has spent the last few years building up Lyft’s mapping assets and capabilities by combining many internal and external data sources and services into an increasingly powerful and mission-critical technology stack. In doing so, we’ve also enabled new user experiences and features across all of Lyft’s products, including rideshare industry leading firsts like CarPlay, Android Auto, and real-time driver feedback! We are hiring a Software Engineer to join our Mapping experiences team that builds end user features to enhance drivers and riders experience on Lyft’s platform by using our in house navigation system. We are looking for an engineer with expertise in system architecture, cross team collaboration, and experience in building scalable solutions in the cloud environments. In this role, you'll collaborate with engineering, product, data science, analytics, operations, and AI/ML teams on programs that empower us to iterate quickly, delighting our passengers and drivers with rideshare focused mapping experiences. Responsibilities: Drive high-impact projects and innovate new solutions to provide the best user experience Lead large features from idea to positive execution and launch Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and distribute knowledge, as well as on call rotations Share your knowledge by giving brown ba

Staff Software Engineer - Testing & Automation Exceptional software engineering is challenging. Amplifying it to ensure that multiple teams can concurrently create and manage a vast, intricate product escalates the complexity. As a Staff Engineer within the Verification Platform team at Sumo Logic, you will drive the implementation and optimization for our verification platform as well as the modernization of our CI/CD pipelines. Your mission is to develop and sustain automated tooling for all testing, verification, and functional requirements, leveraging AI reasoning and machine learning models to predict and prevent delivery issues, while integrating advanced security validation and non-functional requirements into our delivery lifecycle. You will contribute significantly to establishing automated delivery pipelines, empowering autonomous teams to create independently deployable services, and progressing Sumo Logic’s internal Platform-as-a-Service. This role sits at the intersection of Platform Engineering, Quality Engineering, DevSecOps, and Developer Productivity, helping teams deliver secure, reliable, and independently deployable services at scale. Responsibilities Strategy & Leadership: Drive technical direction and design for a modern Quality Engineering platform, driving the adoption of AI reasoning for enhanced automation of all testing, verification, and functional requirements. Pipeline Modernization: Lead the modernization of CI/CD pipelines to include automated security validation, compliance checks, and other critical non-functional requirements, with a focus on integrating AI/ML for intelligent pipeline optimization and risk prediction. Framework Ownership: Own the delivery pipeline and release automation framework for all Sumo services, ensuring improvements in developer productivity, deployment frequency, and release reliability. Cross-Team Collaboration: Educate and collaborate with teams during design and development phases to ensur

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values . This position is based out of our India Development Center in Hyderabad. Who we are looking for Join Truveta’s Intelligence Platform and Applications (IPA) team to build the next wave of healthcare AI — developing adaptive agentic systems and fine-tuned foundation models that continuously learn, reason, and accelerate real-world impact. Guided by Truveta’s mission of Saving Lives with Data, you’ll help transform how health data becomes intelligence, powering breakthroughs that enable researchers, clinicians and operational managers to make data-driven, proactive, and impactful decisions. We firmly believe that patients, doctors, and medical researchers deserve to benefit from the artificial intelligence revolution that is transforming productivity, creativity, and communication. You’ll help shape the AI capabilities that make healthcare more intelligent, efficient, and equitable — driving real-world impact across research, care delivery, and patient outcomes. If you’re seeking a sense of purpose and are motivated to advance how AI supports learning, decision-making, and discovery in healthcare, you’ll find this an inspiring place to grow. We are seeking AI Engineers who thrive at the intersection of agentic and applied AI, machine learning, and large-scale engineering. You’ll blend ML craftsmanship with platform engineering excellence to create scalable, self-improving AI agents and models that learn from vast, diverse healthcare data and deliver meaningful insights through

Zoox is looking for an experienced software engineer to work on large-scale simulation pipelines used to validate the behavior of the Zoox self-driving vehicle. These are data and GPU intensive workloads built on Ray.io and Kubernetes. Given the massive scale and criticality of these pipelines, ensuring their reliability and efficiency has a significant impact on the company's ability to safely and quickly iterate on autonomy development. We are a small, scrappy team within the larger Autonomy organization. Although this role primarily involves off-vehicle pipelines, you will work closely with engineers developing the on-vehicle algorithms and models in our autonomy stack. We stay close to the end users - autonomy engineers - and think about the end to end use case for these validation pipelines. This is a hands-on role with a high degree of independence and ownership. You will be expected to contribute towards the framework’s architecture, reliability, efficiency, and grow its capabilities to support new use cases. You should have a track record of keeping production systems running with high availability. Experience with robotics or autonomous systems is not required but an understanding of the robotic data lifecycle is preferred. In this role, you will: Improve the cost efficiency, reliability, and performance of our validation and simulation pipelines Create production-grade APIs, SDKs, and tools to enable a varied set of validations of autonomous behaviors Improve the ML training pipelines supporting the autonomous behavior org Qualifications Bachelor’s degree in Computer Science or related field and 6+ years of industry experience Experience optimizing large-scale distributed systems for cost and efficiency Experience with AWS or similar providers Proficiency with Python and familiarity with C++ Bonus Qu

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role On the Accelerators team, you will help OpenAI evaluate and bring up new compute platforms that can support large-scale AI training and inference. Your work will range from prototyping system software on new accelerators to enabling performance optimizations across our AI workloads. You’ll work across the stack, collaborating with both hardware and software aspects - working on kernels, sharding strategies, scaling across distributed systems, and performance modeling. You'll help adapt OpenAI's software stack to non-traditional hardware and drive efficiency improvements in core AI workloads. This is not a compiler-focused role, rather bridging ML algorithms with system performance - especially at scale. In this role, you will: Prototype and enable OpenAI's AI software stack on new, exploratory accelerator platforms. Optimize large-scale model performance (LLMs, recommender systems, distributed AI workloads) for diverse hardware environments. Develop kernels, sharding mechanisms, and system scaling strategies tailored to emerging accelerators. Collaborate on optimizations at the model code level (e.g. PyTorch) and below to enhance performance on non-traditional hardware. Perform system-level performance modeling, debug bottlenecks, and drive end-to-end optimization. Work with hardware teams and vendors to evaluate alternatives to existing platforms and adapt the software stack to their architectures. Contribute to runtime improvements, compute/communication over

P-1416 Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse ( CIDR 2021 paper ), open platforms that unify data warehousing and advanced analytics. This new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. To achieve this vision, Databricks is building the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance. Yet we will retain the expressiveness and robustness of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science. You will be part of this multi-year journey. As part of this team, you will design these next-generation systems that leapfrog state-of-the-art within the following areas: Query compilation and optimization Distributed query execution and scheduling Vectorized execution engine Data security Resource management Transaction coordination Efficient storage structures (encodings, indexes) Automatic physical data optimization The responsibilities you will have: Drive requirements clarity and design decisions for ambiguous problems Produce technical design documents and project plans Develop new features Mentor more junior engineers Test and rollout to production, monitoring. What we look for: A passion for database systems, storage systems, distributed systems, language design, or performance optimization Are comfortable working towards a multi-year vision with incremental deliverables Be customer-oriented and focused on having an impact 7+ years of experience working in a related system Optional: PhD in databases or distributed systems About Dat