Performance Modeling Engineer Jobs

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron’s DRAM Design Engineering Group (DDEG) is where innovation meets excellence. We are advancing memory and storage technologies through collaborative engineering and creative problem-solving. Our team works at the forefront of semiconductor design, developing solutions that shape the future of memory products in a fast-paced, learning-focused environment. As a Design Verification Engineer, you will help develop next-generation memory technologies by verifying and optimizing digital and analog circuit designs. In this role, you will work closely with global multi-functional teams across the product lifecycle to deliver high-quality, manufacturable memory solutions that meet performance, reliability, cost, and customer requirements. Your work will directly contribute to bringing advanced memory products from concept to production. Responsibilities: Verify circuit functionality, reliability, power, and compliance with product specifications Drive verification planning, coverage closure, circuit debug, and design improvements Perform circuit modeling and simulation using industry-standard tools Support silicon validation, reticle experiments, and tape-out activities Partner with engineering, manufacturing, and product teams to deliver manufacturable designs Minimum Qualifications: Bachelor’s degree in Electrical Engineering or a related field 4+ years of semiconductor design, verifi

Senior Low Observables (LO) Mission Systems Integration Engineer Company: The Boeing Company The Senior LO Mission Systems Integration Engineer will lead design, integration, analysis, test, and production activities for low observable materials, structures, apertures, sensors, and radomes for mission systems. The role requires strong technical leadership, independent execution of complex tasks, advanced use of computational electromagnetic (CEM) solvers, and the ability to produce and defend technical results with minimal oversight. Key Responsibilities Lead design, modeling, and analysis efforts for LO materials, coatings, structures, and integrated mission systems to meet signature reduction and performance requirements. Independently apply CEM solvers (e.g., FEKO, HFSS, CST, WIPL‑D, xFDTD, or equivalent) to model antennas, apertures, radomes, and LO treatments; perform design optimization and trade studies. Drive integration of LO treatments with mechanical, thermal, and sensor/antenna system constraints; identify and mitigate producibility, testability, and sustainment risks. Plan, execute, and oversee laboratory and field tests (anechoic chamber measurements, antenna/radome characterization, RCS measurements); lead data collection, reduction, and validation activities. Develop and validate predictive models, reconcile simulations with measurements, perform uncertainty quantification, and provide actionable recommendations to engineering and program leadership. Produce high-quality technical documentation: test plans, test reports, technical memoranda, design reviews, and customer briefings. Mentor and provide technical oversight to junior engineers and technicians; ensure adherence to engineering processes, qual

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a Sr. Studio Software Engineer for Roblox Studio Platform, you will be a key contributor to the evolution of Roblox Studio, the primary IDE for making massive multiplayer online games on the Roblox platform. Studio provides the mission-critical tools for 3D modeling, animation, and the complete SDLC for millions of developers. We are looking for engineers who thrive on an adventure into the unknown and have experience across various systems, Operating Systems, Game Engines, and Application Frameworks. You’ll tackle projects involving: Core User Features: Architecting application frameworks, windowing systems, and code generation. “AI Native” Features: Pioneering scalable systems that extend to complex, agentic use cases. Foundational Architecture: Driving OS integration, extensibility, and customizability at the deepest levels. Central Backend Systems: Engineering the infrastructure to power a consistent, high-performance UX. Design Evolution: Collaborating with UX designers to translate Studio into a modern, consistent design language. You Will: Design and execute the technical direction to drive the future extensibility and adaptability of the application. Own and deliver complex techn

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. The Cortex team is building the future of AI for enterprise data. This role focuses on the Search infrastructure that powers our flagship products like CoWork, Cortex Code & Cortex Agents fast, reliable, scalable and secure at the enterprise level. You will be building high-performance retrieval engines (leveraging vector search, hybrid search, and semantic indexing) that power Snowflake Cortex. This involves optimizing how billions of rows of data are indexed and retrieved in milliseconds. What you will do in this role: Architect Agentic Runtimes: Build and scale the orchestration engines that execute complex agentic workflows, ensuring low-latency tool execution and robust state management. Scale Context Engineering Infra: Design high-performance systems for RAG (Retrieval-Augmented Generation), including vector database integration, scalable and efficient search indexing, query processing, and result ranking, semantic caching, and automated metadata extraction. Build the "Evals Engine": Develop the automated infrastructure required to run massive-scale golden set simulations, error analysis pipelines, and "hillclimbing" experiments. Productionize AI Workflows: Collaborate with the modeling team to take raw LLM capabilities and turn them into hardened, multi-tenant mi

At Playlist, life's richest moments happen when people step away from screens to move, connect, explore, and play. We're building the definitive platform for intentional living, connecting people with inspiring experiences in fitness, wellness, and beyond. With popular brands like Mindbody and ClassPass, Playlist empowers businesses and individuals, making it effortless for aspirations to become actions. Join us in reshaping technology's role to foster meaningful, real-world connections. Mindbody equips wellness entrepreneurs with technology to support thriving businesses and create exceptional experiences. Innovation and curiosity drive our culture, connecting businesses and individuals through cutting-edge solutions. Join us if you're passionate about enhancing wellness through technology. The Role You'll Play At Mindbody, Core Engineering builds and evolves the foundational systems that help our products run reliably at scale. In this staff role, you’ll bring clarity to complex technical problems, guide architecture, and strengthen how we design, deliver, and operate the backend services that power real-world experiences. Lead cross-team technical execution, aligning architecture and delivery across multiple squads and core domains Design and evolve microservices patterns that improve reliability, performance, and maintainability Drive cloud and deployment improvements across AWS, Mindbody’s cloud platform, and our containerized deployment environment Partner with engineering and product leaders to turn ambiguous problems into clear technical plans and milestones Establish and socialize standards for service design, APIs, and relational data modeling (SQL) Strengthen monitoring and operational visibility using New Relic and Kibana, turning insights into durable system improvements Mentor and unblock engineers through design reviews, pairing, and practical guidance Reduce technical risk and complexity while balancing

The Data Engineering team’s mission is to ensure high-quality data to enable data-informed decision-making across Asana. You will build data artifacts that are leveraged by Product and Business Data Science teams to optimize our user adoption, growth, and experience. In this role, you will partner with the Infrastructure team to build a self-service analytics platform for the company. This role is based in our Vancouver office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday; most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Design, implement, and scale end-to-end data products that support growing data processing and analytical needs Transform raw data into actionable insights to drive product strategy and power in-depth analyses and reporting Leverage AI to build self-serve tools and accelerate Data/GTM workflows Partner with data scientists, domain experts, and engineering teams to develop a roadmap that aligns with our business goals Implement systems that guarantee data quality, governance, and availability About you 5+ years of experience in Data Engineering or Software Engineering Experience in data modeling and building scalable data pipelines involving complex transformations Proficiency in data processing and storage technologies like Databricks, AWS/S3, Python/Scala/Java, SQL, Spark, and Airflow Proactive and innovative in identifying and addressing performance bottlenecks in existing workflows Motivated to work closely with cross-functional partners to evolve our analytical data model Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making At Asana, we're com

MongoDB is building a world-class team in North America to create tooling that helps customers modernize their applications and migrate their data from legacy relational databases to MongoDB in real-time. As companies modernise legacy workloads and data ecosystems, they are increasingly drawn to the flexibility and scalability of the document model. The tools developed by the Code Generation and Data Migration team are critical in this journey, helping customers with schema modeling, code generation, initial data loads, and continuous data synchronization. We're looking for a Software Engineer with a strong background in computer science fundamentals, systems design, experience in the Java ecosystem, streaming systems, and data-intensive applications to join our engineering team. In this role, you will be instrumental in designing, building, and optimizing the underlying data structures, algorithms, and database interactions that power our generative AI platform, code generation and migration tools. This involves crafting sophisticated orchestration layers, robust integration points, and high-performance data systems that seamlessly connect and leverage advanced AI capabilities for code generation and building a sophisticated data migration suite using a modern technology stack, which includes Java, Spring Boot, Kafka, Debezium, and React.You will work on critical components that ensure the scalability, efficiency, and reliability of our services, collaborating closely with AI researchers, product management and other engineers to design and implement cutting-edge products that solve complex customer challenges. This role will be based out of Washington, Oregon, or California. The ideal candidate for this role will have 2+ years of engineering experience in backend systems, distributed systems, or core platform development Experience in one or several of Java, Rust, C/C++, and/or Python, with a strong understanding of systems-level programming, memory ma

Engineer 3, Business Systems (CPQ) We are looking to speak to candidates who are based in Gurugram for our hybrid working model. About Team The CRM Technologies Team plays a critical role in optimizing our sales processes, streamlining customer interactions, and maximizing the efficiency of our sales efforts. By leveraging Salesforce and Quote-to-Cash technologies, the team ensures that business users have the tools, automation, and operational support needed to effectively manage quoting, pricing, approvals, and downstream business processes. With deep expertise in Salesforce development, CPQ, integrations, and platform operations, the team continuously enhances the CRM ecosystem to meet evolving business needs. The team partners closely with stakeholders across Sales Operations, Revenue Operations, Finance, Deal Desk, and Engineering to deliver scalable, secure, and reliable Quote-to-Cash solutions. Role Overview We are looking for a CPQ Engineer III to design, build, and support core capabilities in our Configure–Price–Quote (CPQ) stack that power how our GTM teams sell and price MongoDB offerings. As a senior individual contributor, you will own end-to-end delivery of features across configuration, pricing, discounting, approvals, and quote generation, working closely with Product, Deal Strategy, RevOps, and Sales. You will translate business requirements into high-quality technical solutions on Salesforce CPQ and related platforms, spanning configuration, custom development (Apex/LWC/Flows), and integrations with downstream systems. This role is hands-on and delivery-focused: you will be responsible for implementing well-structured, testable solutions, improving performance and reliability of existing CPQ flows, and contributing to shared patterns, frameworks, and best practices within the CPQ & RevOps engineering team. What you’ll do Design, build, and support Salesforce solutions across product modeling, pricing, quoting, approvals, amendments, and renewa

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Senior Analytics Engineer As a Senior Analytics Engineer on the Platform team, you'll build the scalable data models and pipelines that power analytics, experimentation, and decision-making across Coinbase. Our Analytics Engineering team transforms raw data into trusted, well-modeled sources that stakeholders across Product, Engineering, and Data Science rely on daily. You'll own end-to-end data solutions for specific business domains, turning complex data flows into clean, reusable frameworks that unlock commercial value at scale. What you'll do: Own end-to-end data modeling for assigned business domains, from understanding source system data flows through designing modular, reusable models (star/snowflake schemas) that serve as the single source of truth for downstream teams. Build and optimize ETL/ELT pipelines using modern tools like dbt and Airflow, ensuring data quality, reliability, and performance at scale across Snowflake or similar warehouse architectures. Partner with Engineering, Product, and Data Science teams to identify data gaps, define requirements, and deliver data products that directly enable experimentation, ad hoc analysis, and business metric optimization. Develop scalable abstractions and frameworks (UDFs, Python packages, internal data apps) that multiply the efficiency of other data teams and reduce time-to-insight across the organization. D

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve people's lives. About the Role We are seeking a lead thermal simulation engineer to help accelerate the design and development of next-generation robotic systems through modeling, simulation, and analysis. You will work closely with mechanical, electrical, controls, and robotics engineers to evaluate designs before hardware is built, identify risks early, and guide critical architecture decisions. This role spans structural and thermal analysis and design across robotic subsystems including actuators, mechanisms, structures, electronics, and integrated systems. You will develop simulation workflows that improve engineering velocity, increase confidence in design decisions, and help us build more capable, reliable, and manufacturable robotic platforms. This role is based in San Francisco, CA. This role will be expected to be in office 4 days per week and offer relocation assistance to new employees. In this role, you will: Perform thermal simulations to assess heat generation, cooling strategies, thermal interfaces, and system-level thermal performance Partner with mechanical, electrical, and controls engineers to influence design decisions early in development Build simulation models to evaluate robotic actuators, transmissions, mechanisms, structures, soft goods, and integrated assemblies Correlate simulation results with physical testing and develop methodologies to improve model accuracy Support architecture trade studies by evaluating design concepts before hardware is built Develop simulation workflows, standards, and best practices that scale across the robotics o

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. About Fern, a Postman Company Fern helps software companies build a world-class API experience. Our customers include industry leaders like Nvidia, Square, and Twilio, as well as fast-growing AI companies like ElevenLabs and OpenRouter. In the next year, the majority of API integrations will be implemented by AI agents. Agents don’t read marketing pages. They need strongly typed schemas, structured endpoints, deterministic contracts, and documentation that can be fed into a context window. Our team is small and talent-dense. We’re a team of builders from Google, Palantir, Amazon, and Uber, working together in New York City. About the Role As a Staff Software Engineer at Fern, you’ll build APIs, scale AI infrastructure, and design developer experiences that reach millions of people. Set technical direction: Drive system design decisions around data modeling, performance, correctness, and reliability. Identify scaling bottlenecks before they become problems. Build for durability and scale: Ensure our systems are performant, observable, secure, and resilient under real-world production load across infrastructur

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in artificial intelligence possible! We do it all while committing to integrity, sustainability, and giving back to our communities, because doing so can fuel the very innovation we are pursuing. As a process integration engineer in the DRAM organization, you will be part of a team of world-class engineers who are working in an industry leading 300mm R&D facility on technology which enables future memory scaling. You will focus on the performance and manufacturability of Micron’s cutting-edge next-generation memories. Areas of concentration will include integration and circuit issues specific to DRAM technology. In addition to a broad basis of process integration knowledge, this position will require a strong background in semiconductor device physics. Role interacts significantly with the process development, simulation, modeling, characterization, and reliability groups. Responsibilities include, but not limited to: Lead technology integration activities in enabling manufacturability of state-of-the-art DRAM technology Engage with numerous cross-functional teams including process development, product engineering, design, yield improvement, advanced mask and probe to arrive at solutions to

Job Overview We are looking for an Analytics Engineer who will own dbt Cloud in our organisation and maintain the analytics pipelines built on top of it. You will administer dbt Cloud across multiple independent projects, keep our business-critical pipelines running (including finance data models), and support analysts in other teams as a mentor and go-to person for dbt. Our stack is Snowflake, dbt and AWS, with Python for tooling and automation. We are also building AI-assisted and agentic workflows into our daily work, and you will take an active part in this. Reports to Director of Mobile and New Games What will you do? Administer dbt Cloud for the whole organisation: project setup, environments, permissions, CI/CD, version upgrades and cost control Set up and support multiple independent dbt projects, define common standards and conventions so teams stay aligned Develop and maintain production dbt pipelines, including complex finance models where accuracy and trust are critical Mentor analysts on dbt, SQL modeling, testing and code review Tune Snowflake performance and cost, improve pipeline reliability and monitoring Build tooling and automation in Python (AWS Lambda, S3, orchestration, metadata workflows) Drive AI adoption in our analytics engineering work: build common AI skills for dbt development (documentation, testing, code generation) and automated agentic workflows that the whole team can reuse Follow current trends in AI tooling and agentic systems, evaluate new approaches and bring the useful ones into the team What are we looking for? 4+ years of experience in analytics engineering, data engineering or a similar role Strong hands-on dbt experience, ideally including dbt Cloud administration (projects, environments, jobs, CI/CD), not only model development Strong SQL and data modeling skills Production experience with Snowflake, including performance tuning and cost awareness Python for data tooling and automation Experience with AWS services used in