Performance Modeling Engineer Jobs

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

Propulsion Engineer (Experienced or Senior) Company: The Boeing Company Boeing Defense, Space & Security (BDS) is seeking a Propulsion Engineer to contribute to the development and qualification of a new propulsion system for a cutting-edge fixed-wing program in the St. Louis, MO , area. In this role, you will be an integral part of a larger Flight Sciences team consisting of propulsion, aerodynamics, and guidance, navigation and controls. As part of the propulsion team you will contribute to inlet development, engine integration and controls, testing, and qualification efforts. Come join the Boeing team as we develop next generation airplanes that will make aviation history Our teams are currently hiring for a broad range of experience levels including; Experienced and Senior Level Propulsion Engineer. Position Responsibilities: Defines requirements for propulsion systems within a model-based engineering environment Defines, coordinates and controls the functional and physical interfaces between the propulsion system and the vehicle Configures or designs propulsion sub-systems and components to meet all vehicle design and performance specifications Contributes to or leads a range of testing, analysis, modeling, and simulation activities aimed at predicting and validating system performance Defines and performs verification tests for propulsion sub-systems and components Review, processing and approval of engine and component qualification documentation Assist with propulsion ground and flight test planning Propulsion vendor management and coordination This position is expected to be 100% onsite. The selected candidate will b

About the Role The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding, and ads optimization that shape the future of streaming. We are seeking a VP / Director of Machine Learning Engineering to lead and build a high-performing team while staying close to the technical work. This is a hands-on leadership role: you will set the strategic direction for our recommendation, personalization, and ads optimization systems, including recommendation foundation modeling, and you will stay in the algorithms and the code, conducting deep dives into modeling components and guiding the hardest technical decisions yourself. You will tackle complex machine learning problems at scale and partner closely with cross-functional teams to ship solutions that measurably improve how hundreds of millions of viewers experience Tubi. What You’ll Do Lead, build, and grow a high-performing ML engineering team, fostering a culture of technical excellence, ownership, and rapid iteration. Define and drive the ML strategy and long-term technical roadmap for recommendation, personalization, and ads optimization, including recommendation foundation modeling, identifying opportunities for ML to shape Tubi’s broader product and business strategy. Stay hands-on: conduct deep dives into algorithmic components and systems, ensuring models are optimized for both performance and scalability across regions and product areas. Lead the design, development, and implementation of advanced recommendation systems and algorithms, contributing directly to the most challenging technical problems. Build and deploy robust, full-stack ML pipelines: data extraction, feature development, model training, testing, deployment, and serving. Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring

Who We Are HP IQ is HP’s new AI innovation lab. Combining startup agility with HP’s global scale, we’re building intelligent technologies that redefine how the world works, creates, and collaborates. We’re assembling a diverse, world-class team—engineers, designers, researchers, and product minds—focused on creating an intelligent ecosystem across HP’s portfolio. Together, we’re developing intuitive, adaptive solutions that spark creativity, boost productivity, and make collaboration seamless. We create breakthrough solutions that make complex tasks feel effortless, teamwork more natural, and ideas more impactful—always with a human-centric mindset. By embedding AI advancements into every HP product and service, we’re expanding what’s possible for individuals, organisations, and the future of work. Join us as we reinvent work, so people everywhere can do their best work. About The Role HP IQ is seeking a Senior Power Systems Engineer to drive end to end system architecture, modeling, and optimization for wearable platforms. The candidate will build power models, define system use cases and operating modes, partner with product and engineering teams to meet aggressive power targets, and define manufacturing tests and field telemetry for NPI. The ideal candidate brings strong systems thinking, hands-on experience with low power architectures, and the ability to build models and telemetry to drive tradeoffs from SOC level to board level to maximize user runtime. What You Might Do: Power architecture responsibility for a wearable device covering SoC states, sensor, audio, and memory architecture tradeoffs at board level. Battery, PCM, and charging profile definition and validation Design power experiments, test plans, and measurement & telemetry mechanisms across firmware and hardware to optimize power and performance. Build and maintain system-level power models to model expected power consumption for user profiles. Map power models by subsystem, correlating

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We are looking for an experienced Mechanical Engineer with 7+ years of experience in design of IT hardware from chip/package to system levels. You’ll work alongside experts in thermal, mechanical, electrical, software, and systems engineering to support the design, analysis, and validation of mechanical and thermal systems that ensure the reliability, efficiency, and longevity of mission-critical hardware. This position requires strong analytical skills, hands-on testing experience, and the ability to work in a fast-paced, cross-disciplinary environment. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Lead mechanical design for AI supercomputer product in the data center application Collaborate with the cross functional team to design and optimize thermal solutions for data center hardware, including chips, power modules, and system-level cooling architectures Collaborate with cross-functional teams to integrate thermal management strategies into hardware design, from concept to mass production Design and validate mechanical systems, including chassis, enclosures, cooling systems, and high-power connections, ensuring alignment with performance and reliability standards. Perform 3D modeling, FEA, tolerance analysis, and prototyping, ensuring manufacturability and a

Role Overview We are looking for a Senior FP&A Engineer to lead the design and implementation of enterprise planning solutions across Finance, Sales, and Workforce domains. This role will be part of a Global Finance Technology, partnering closely with onshore FP&A, RevOps, and other Business teams. You will play a key role in driving the organization’s transition to driver-based, integrated planning using platforms such as Pigment, Anaplan, and Workday Adaptive Planning, while ensuring scalability, governance, and high-quality delivery from India. We are looking to speak to candidates who are based in Gurugram or Bangalore for our hybrid working model. Key Responsibilities 1. Enterprise Planning Delivery Design and build scalable planning models across: Financial Planning (P&L, Cash Flow, Balance Sheet) Workforce Planning and Cost modeling Sales & Revenue forecasting (ARR, pipeline, bookings) Own end-to-end delivery working with the Product Manager : design → build → test → deploy → support 2. Model Development & Optimization Build multi-dimensional, driver-based models with strong focus on performance Develop scenario planning, versioning, and forecasting capabilities Optimize model size, calculation efficiency, and user experience 3. Platform Expertise Subject Matter Expertise in: Pigment Anaplan (Model Builder / Solution Architect) Configure workflows, security, and access controls Leverage platform-native capabilities vs over-customization 4. Data Integration & Automation Integrate planning tools with enterprise systems: ERP (NetSuite / Oracle) CRM (Salesforce) Data platforms Build and maintain automated data pipelines using SQL, APIs, or ETL tools 5. Stakeholder Collaboration (Global Model) Work closely with US / EMEA FP&A, IT, and Business teams Participate in requirement workshops and translate business needs into technical designs Provide regular updates, demos, and documentation to global stakeholders 6. Governance, C

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? We're building the data infrastructure behind some of the most demanding AI training workloads in the world, and we want sharp, curious people to help us do it. In this role, you'll build and maintain the high-performance data layer our Modeling teams rely on for training and evaluation jobs. As a Software Engineer, Data Infrastructure, you will: Work directly on petabyte-scale storage infrastructure, and the networking and performance challenges that come with it. Collaborate daily with researchers and engineers who are some of the best in the world at what they do. You may be a good fit if you have: 4+ years of experience working on data storage infrastructure Strong command of Python Kubernetes experience, especially on the storage side (Persistent Volumes, CSI drivers, etc.) The ability to transform unstructured data into performant datasets across diverse storage backends including S3, GCS, and POSIX Experience with distributed data processing frameworks such as Apache Beam, Spark, or Flink [Nice-to-have] Familiarity with modern analytics tooling such as BigQuery, Airflow, or dbt Genuine excitement about AI.

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 CoWork team is defining the future of AI for enterprise data. Our mission is to transform how the world’s largest enterprises interact with their data through flagship products like Snowflake (CoWork) Intelligence . As a Principal AI Engineer , you will be a technical North Star for our AI initiatives. You won't just execute on a roadmap; you will help define it. You will tackle the most complex, "frontier" problems in agentic reasoning, NL-to-SQL, and enterprise-scale RAG, ensuring our AI products are not only innovative but fundamentally reliable and scalable for the Fortune 500. What you will do in this role: Technical Strategy & Architecture: Define the long-term technical vision for Snowflake Intelligence. Lead the architectural design of multi-agent systems, complex tool-use frameworks, and self-correcting NL-to-SQL engines. Drive Industry-Leading Reliability: Move beyond simple evals to build world-class, automated "hill-climbing" infrastructure. You will establish the methodology for how Snowflake measures and guarantees LLM performance across diverse customer schemas. Cross-Functional Influence: Partner with Product and Engineering leadership to align AI capabilities with business goals. You will bridge the gap between Research (modeling) and Product

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Senior Database Reliability Engineer (DBRE) Experience Level: Mid–Senior (4+ years PostgreSQL experience) About the Role We are looking for a highly skilled Database Reliability Engineer (DBRE) with deep expertise in PostgreSQL at scale and solid experience with MySQL. In this role, you will design, operationalize, and optimize the data persistence layer that powers our large-scale, mission-critical systems. You will work closely with SRE, Platform, and Engineering teams to ensure performance, reliability, automation, and operational excellence across our database environment. This is a hands-on engineering role focused on building resilient data infrastructure, not just administering it. Responsibilities: Architecture, Reliability & Performance Design, implement, and operate highly available PostgreSQL clusters (physical replication, logical replication, sharding/partitioning, failover automation). Optimize query performance, indexing strategies, schema design, and storage engines. Perform capacity planning, growth forecasting, and workload modeling. Own high-availability strategies including automatic failover, multi-AZ/multi-region setups, and disaster recovery. Automation & Tooling Develop automation for any and all tasks including but not limited to: provisioning, configuration, backups, failovers, vacuum tuning, and schema management using tools such as Terraform, Ansible, Kubernetes Operators, or custom tooling. Build monitoring, alerti

About the Team The Personal AGI team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and potential future products. In the Model Experience team, we shape the default character and behavior of ChatGPT: how the model communicates, responds to users, uses its capabilities, and behaves across different contexts and languages. Our goal is to make every interaction with ChatGPT thoughtful, helpful, and trustworthy. We take an opinionated view of what good human–AI interaction should look like, then turn that vision into real model behavior through human data, evaluations, reward models, and post-training. Our work sits at the intersection of research, product, and model design. We partner closely with teams across OpenAI to conduct research and ensure our models are thoughtful, safe, reliable to serve millions of users. About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models. Our team works in research areas combining reinforcement learning and products. We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research and the quality of human-AI interaction. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own and pursue a research agenda to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. You might thrive in this role if you: Have a deep understanding of machine learning and machine learning applications. Have good judgment about model behavior and can communicate this judgment effec

About the Team The Personal AGI team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and potential future products. The team partners closely with research and product teams across the company, and conducts research as a final step to prepare for real world deployment to millions of users, ensuring that our models are safe, efficient, and reliable. About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models. Our team works in research areas combining reinforcement learning and products. We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own and pursue a research agenda to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. You might thrive in this role if you: Have a deep understanding of machine learning and machine learning applications. Have a working knowledge of relevant models, and building evaluations for model capability improvement. Are comfortable diving into a large ML codebase to debug. Thrive in a dynamic and technically complex environment. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and

About the Team The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model–system interfaces with the core search stack (serving, indexing, retrieval) to translate model intent into reliable, real-world actions. Operating at the frontier of AI and information retrieval, the team develops large-scale systems that transform and index vast corpora, enabling models to reason over global knowledge and act dependably. In close partnership with researchers, we rapidly bring modeling breakthroughs into production and redefine how intelligent systems discover, retrieve, and synthesize information at planetary scale. About the Role We’re looking for a Software Engineer focused on building and scaling retrieval systems. You’ll work with a team of researchers and engineers to develop infrastructure that enables models to retrieve and act on the right information at the right time. This includes designing and operating indexing systems, retrieval pipelines, and serving layers. This work supports retrieval across OpenAI products and research, with direct impact on system performance, reliability, and scale. Responsibilities Build and scale retrieval infrastructure across indexing, serving, and query execution. Develop low-latency, high-throughput systems for real-time model interaction. Partner with research to productionize embedding and retrieval techniques. Support dense, sparse, and hybrid retrieval pipelines. Own system performance, reliability, and observability at scale. Collaborate across Pretraining, Inference, and Product teams to integrate retrieval end-to-e

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. At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers who are energized by the opportunity to reinvent how they work. The Cortex Apps team is building the future of AI for enterprise data, and this role focuses on the backend infrastructure that powers our flagship products like Snowflake Intelligence, Cortex Agents, and Search. You won't just be using AI tools; you will be building the high-performance systems that orchestrate them, making agentic AI fast, reliable, scalable, and secure at the enterprise level. What you will do in this role: Build Agentic Runtimes: Help build and scale the orchestration engines that execute complex agentic workflows, ensuring low-latency tool execution and robust state management. Scale Context Engineering Infra: Develop and design high-performance systems for RAG (Retrieval-Augmented Generation), including vector database integration, scalable search indexing, query processing, and semantic caching. Develop the "Evals Engine": Build the automated infrastructure required to run massive-scale golden set simulations, error analysis pipelines, and experiments. Productionize AI Workflows: Collaborate with the modeling team to take raw LLM capabilities and turn them into hardened,

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. For over 180 years, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. Sr. Data Cloud Engineer(s)(multiple positions) – Duties are using relational database systems, CI/CD pipeline, Kubernetes for application deployments, terraform IAC, Observability using Splunk, server-side GitHub REST API, & Snowflake, Spark, & Python to design, automate, implement & maintain data architecture patterns in AWS & GCP for data collection infrastructure & pipelines for multi-region cloud-based big data IaaS & PaaS solutions including performing requirements & document use technology analysis; coordinating data integration & ETL processes; supporting data security, integrity & cost controls; automating data processes utilizing Cloud Composer & develop SQL scripts for data modeling; performing end-to-end pipeline load performance testing; supporting technology upgrades through PostgreSQL & Cloud SQL cloud migrations; performing SQL & NoSQL database tuning & maintenance; providing guidance on data management & SQL optimization; & developing data warehousing management policies. Requires Bach degree in Comp Science, Comp Engineering, Information Technology (IT) or related field & 5 yrs exp in job duties as stated. Position is with Dun & Bradstreet in Jacksonville, FL. Inquire and send resume through Dun & Bradstreet’s job board at https://jobs.lever.co/dnb. Position is under Sr. Data Cloud Engineer for Jacksonville, FL. #LI-DNI

Join Truecaller – The place where innovation meets impact! Truecaller's mission is to build trust in communication by making it safer, smarter, and more efficient. Born in Sweden, trusted by the world, and here’s why we stand out: We are trusted by over 500 million active users every month across 190+ countries We identify over 15 billion calls daily, helping users avoid spam and scams We are powered by a team of 400+ employees from 45+ nationalities We always look for people who take initiative, own their work, and keep raising the bar. An entrepreneurial mindset matters here, especially when it turns bold ideas into real actions. We stay collaborative and focused, always searching for smarter paths forward. If you want to make an impact and grow with a team that inspires millions, you’ll fit right in. As an Engineering Manager, you will lead the team behind Truecaller's Recommendations and adVantage, our AI-powered performance advertising platform. It is a multi-disciplinary team of ML engineers, data scientists, backend engineers, and data engineers building the retrieval, ranking, and contextual-bandit systems, and the real-time serving and data infrastructure beneath them, that decides what Truecaller recommends and shows to hundreds of millions of users. The role sits at the intersection of technical depth and people leadership: you will set direction across an applied-ML stack, keep a highly specialized team healthy and growing, and turn a research-heavy roadmap into shipped, reliable systems. What you'll do: Lead, grow, and retain a high-performing team of ML engineers, data scientists, backend engineers, and data engineers, investing deliberately in each person's development and career path. Set technical direction across the recommendation and advertising ML stack - retrieval, ranking, contextual bandits, and conversion modeling - along with the real-time serving and data platforms that support them. Own team planning, prioritization, and delivery, balanci