Production Supervisor Jobs

P-1415 At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, Databricks has started a multi-year journey to build the best Data Intelligence Platform. For this we are building on top of a great foundation but our goal is to go further to build dramatically better products. We want to revisit every component to provide our customers with the fastest, easiest to use and most secure data platform for all their data workloads. As a software engineer, you will join as a founding member of not only the Belgrade site, but really as a founding team for our multi-year journey to achieve our Lakehouse vision. You will be involved in the entire development cycle and exemplify all core Databricks values. The impact you'll have: Our backend teams span many domains across our essential service platforms. For instance, you might work on challenges such as: Problems that span from product to infrastructure including: distributed systems, at-scale service architecture and monitoring, workflow orchestration, and developer experience. Build reliable, secure and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, GCS, Azure Blob Store. Develop product features that empower our customers to easily store and access their data. What we look for: BS (or higher) in Computer Science, or a related field 5+ years of production level experience in one of: Java, Scala, C++, or similar language Experience developing large-scale distributed systems Experience working on a SaaS platform or with Service-Oriented Architectures Knowledge of SQL About Databricks Databricks is the D

P-1414 At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, Databricks has started a multi-year journey to build the best Data Intelligence Platform. For this we are building on top of a great foundation but our goal is to go further to build dramatically better products. From the Storage Engine (data layout, encryption, caching, ...) to the Query Engine (Vectorization, Query Optimization, …), we want to revisit every component to provide our customers with the fastest, easiest to use and most secure data platform for all their data workloads. As a software engineer, you will join as a founding member of the not only the Belgrade site, but really as a founding team for our multi-year journey to achieve our Lakehouse vision. You will be involved in the entire development cycle and exemplify all core Databricks values (own-it, data decide, teamwork, customer-obsessed). 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: BS in Computer Science or equivalent practical experience in databases or distributed systems Comfortable working towards a multi-year vision with incremental deliverables Motivated by delivering customer value and impact 3+ years of production level experience in either Java, Scala or C++ Solid foundation in algorithms and data structures and their real-world use cases Experience with distributed systems, databases, and big data systems (Apache Spark™, Hadoop) About Databricks Databricks is the Data and A

P-1414 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 5+ years of experience working in a related system Optional: PhD in databases or distributed systems About Databricks

P-1414 At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, Databricks has started a multi-year journey to build the best Data Intelligence Platform. For this we are building on top of a great foundation but our goal is to go further to build dramatically better products. We want to revisit every component to provide our customers with the fastest, easiest to use and most secure data platform for all their data workloads. As a software engineer, you will join as a founding member of not only the Belgrade site, but really as a founding team for our multi-year journey to achieve our Lakehouse vision. You will be involved in the entire development cycle and exemplify all core Databricks values. The impact you'll have: Our backend teams span many domains across our essential service platforms. For instance, you might work on challenges such as: Problems that span from product to infrastructure including: distributed systems, at-scale service architecture and monitoring, workflow orchestration, and developer experience. Build reliable, secure and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, GCS, Azure Blob Store. Develop product features that empower our customers to easily store and access their data. What we look for: BS (or higher) in Computer Science, or a related field 3+ years of production level experience in one of: Java, Scala, C++, or similar language Experience developing large-scale distributed systems Experience working on a SaaS platform or with Service-Oriented Architectures Knowledge of SQL About Databricks Databricks is the Data and

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 We are looking for a Machine Learning Scientist (LLM & Agents) to join the Enterprise Solution Science Team. This team focuses on applying cutting-edge ML technologies to real-world marketing problems by combining them with omnichannel customer data. In this role, you will own agent features end to end — from problem definition and design, to shipping, to measuring and improving quality in production. What You’ll Work On You will contribute to the design, development, and productionization of one or more enterprise AI agents, including: Marketing Agent: Empower marketers to improve conversion rates and drive revenue growth. Strategy Agent: Transform raw data into actionable, revenue-driving strategies and high-potential audience segments. Data Analysis Agent: Answer business questions by planning multi-step analyses and running SQL over large customer datasets, with every number traceable to the query that produced it. Sales and Service Agent: Drive sales conversion, increase average order value (AOV), and deepen brand engagement and customer loyalty through real-time, 24/7 AI-powered support. Build agent capabilities as reusable skills and MCP tools, and design tool interfaces that agents use correctly and efficiently Bring predictive models (e.g. propensity, churn, recommendation) into agent workflows and next-best-action suggestions Build evaluation — test sets, LLM-as-a-judge, production trace review — and use it to decide what ships Make agents faster and cheaper without losing answer quality, through c

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team Our team is organized around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier. About the role As a Research Engineer on our team you will work end to end across the whole model stack, identifying and addressing key infra blockers on the path to scientific AGI. Strong candidates should have familiarity with elements of language model training, evaluation, and inference and eagerness to quickly dive and get up to speed in areas they are not yet an expert on. This may include performance optimization, distributed systems, VM/sandboxing/container deployment, and large scale data pipelines. Join us in our mission to develop advanced AI systems pushing the frontiers of science and benefiting humanity. Responsibilities: Design and implement large-scale infrastructure systems to support AI scientist training, evaluation, and deployment across distributed environments Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities Develop robust and reliable evaluation frameworks for measuring progress towards scientific AGI. Build scalable and performant VM/sandboxing/container architectures to safely execute long-horizon AI tasks and scientific workflows Collaborate to translate experimental requirements into production-ready infrastructure Develop large scale data pipelines to handle advanced language model training requirements Optimize large scale training and inference pipelines for stable and efficient reinforcement learning You may be a good fit if you: Have 6+

Lead AI Engineer (Senior/Principal Consultant) Location: London (Hybrid) | Practice Area : Technology & Engineering | Type: Permanent Empower the next frontier of AI with Capco. Shape, build, and deliver future-ready generative systems. The Role We’re looking for a Lead AI Engineer (Senior/Principal Consultant) to join our Technology Delivery Team. You’ll combine your expertise in AI/ML engineering and software development to build and deploy cutting-edge generative AI and agentic systems across the financial services sector. As a hands-on leader, you’ll architect AI solutions, embed them within enterprise environments, and drive impactful outcomes through advanced engineering, scalable pipelines, and deep cross-functional collaboration. What You’ll Do Architect and develop autonomous AI systems integrating multi-modal LLMs (text, image, audio, video) Design agentic workflows enabling AI agents to interact with data sources and APIs using prompt engineering and RAG Fine-tune, optimize, and deploy large language and multi-modal models with a focus on performance and latency Build scalable MLOps pipelines and full-stack applications to support robust, production-grade AI deployments Guide multidisciplinary teams and clients through strategic decisions in AI engineering and GenAI adoption What We’re Looking For Bachelor’s degree or higher in Computer Science, AI, or related STEM fields Hands-on experience deploying LLMs and multi-modal models at scale Strong engineering background in Python with proven backend and API development skills Solid understanding of scalable MLOps, observability, and cloud-native AI deployment Excellent communication, problem-solving, and project management skills in agile environments Bonus Points For Experience with agentic frameworks (e.g., LangChain, LlamaIndex) Experience in deep learning frameworks and front-end development Familiarity with Langfuse, Langsmith, or other LLM observability tools Understanding of Model Context Protocol

P-1328 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As a software engineer with a backend focus, you will work with your team to build infrastructure and products for the Databricks platform at scale. The impact you'll have: Our backend teams span many domains across our essential service platforms. For instance, you might work on challenges such as: Problems that span from product to infrastructure including: distributed systems, at-scale service architecture and monitoring, workflow orchestration, and developer experience. Deliver reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store. Build reliable, scalable services, e.g. Scala, Kubernetes, and data pipelines, e.g. Spark, Databricks, to power the pricing infrastructure that serves millions of cluster-hours per day and develop product features that empower customers to easily view and control platform usage. What we look for: BS (or higher) in Computer Science, or a related field 7+ years of production level experience in one of: Java, Scala, C++, or similar language. Experience developing large-scale distributed systems. Experience working on a SaaS platform or with Service-Oriented Architectures. Good knowledge of SQL. About Databricks Databricks is the Data and AI company. More than 20,000 organizatio

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. In this role, you will: Collaborate with the sales leadership to understand customer requirements and enable technical solutions deployment based on customer needs. Develop an in-depth understanding of Ema’s technology and underlying architectures Deliver compelling product demonstrations tailored to the specific needs of potential customers, showcasing key features and benefits. Work closely with customers to execute successful PoCs, demonstrating the feasibility and value of Ema in their environment. Position yourself as a Trusted Advisor to key customer stakeholders with a focus on achieving their desired Business Outcomes. Collaborate with customers to design and architect solutions that align with their business goals, ensuring seamless integration with existing systems. Drive project teams towards common goals of accelerating the adoption of Ema’s solutions. Demonstrate and communicate the value of Ema’s solution throughout the engagement, from demo to proof of concept to running workshops, design sessions and implementation with customers and stakeholders. Help take Ema’s solution from POC to production. Understand customers cloud/on-prem environmen

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team Our team is organized around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier. Our team likes to think across the whole model stack. Currently the team is focused on improving models' abilities to use computers – as a laboratory for long horizon tasks and a key blocker to many scientific workflows. About the role As a Research Engineer on our team you will work end to end, identifying and addressing key blockers on the path to scientific AGI. Strong candidates should have familiarity with language model training, evaluation, and inference, be comfortable triaging research ideas and diagnosing problems and enjoy working collaboratively. Familiarity with performance optimization, distributed systems, vm/sandboxing/container deployment, and large scale data pipelines is highly encouraged. Join us in our mission to develop advanced AI systems that are both powerful and beneficial for humanity. Responsibilities: Working across the full stack to identify and remove bottlenecks preventing progress toward scientific AGI Develop approaches to address long-horizon task completion and complex reasoning challenges essential for scientific discovery Scaling research ideas from prototype to production Create benchmarks and evaluation frameworks to measure model capabilities in scientific workflows and computer use Implement distributed training systems and performance optimizations to support large-scale model development You may be a good fit if you: Have 8+ years of ML research experience Are

P-1408 The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products . Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. As our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. In 2025, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale. Key Responsibilities Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. Contribute to building a robust framework for evaluating search ranking improvements - both offline and online. What We’re Looking For BS+ (M.S. or PhD preferred) in Computer Science, or a related field. 10+ years experience developing search relevance systems at scale in production or in high-impact research environments. Experience applying LLM to search relevance Experience in one or more of the following: Query understanding NLP Text mining Recommendations Personalization Discovery Conversational AI Strong understanding of computer science fundamentals. Contributions to well-used open-source projects. Why Join Us? At Databricks,

P-1408 The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. As our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. In 2026, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale. Key Responsibilities Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. Contribute to building a robust framework for evaluating search ranking improvements - both offline and online. What We’re Looking For BS+ (M.S. or PhD preferred) in Computer Science, or a related field. 10+ years experience developing search relevance systems at scale in production or in high-impact research environments. Experience applying LLM to search relevance Experience in one or more of the following: Query understanding NLP Text mining Recommendations Personalization Discovery Conversational AI Strong understanding of computer science fundamentals. Contributions to well-used open-source projects. Why Join Us? At Databricks, w

About the team Online Data builds and operates Habitat, the single product surface of Online Data and the system of record for OpenAI’s online user data. As OpenAI’s scale and product requirements evolve, Habitat is becoming a full-stack, one-size-fits-most database platform with end-to-end ownership of: Provisioning and developer experience APIs and guardrails Scaling, performance, and reliability Data movement, caching, routing, and placement Privacy enforcement and access control Change Data Capture (CDC) as a first-class primitive The foundation for future storage backends You’ll work on the core online database platform behind OpenAI’s products, building and operating Habitat services that handle high-QPS, latency-sensitive workloads across regions. You’ll partner closely with internal platform and product teams to ship safe, reliable systems, then push them to be faster and more cost-efficient through better caching, routing, observability, and operational tooling. This is a critical role for engineers who like owning hard distributed-systems problems end to end and sweating the details from p99 latency to production operations at massive scale. In this role, you will Design and build core abstractions spanning storage, caching, routing, CDC, and privacy enforcement Own a major surface area end to end, from product and API design to operational excellence Improve latency, correctness, and cost efficiency for real production workloads at massive scale Build strong instrumentation, debugging workflows, and developer-first tooling Collaborate closely with internal product and infrastructure teams to understand requirements and ship pragmatic solutions Participate in an on-call rotation and raise the bar on reliability while aggressively improving performance and usability You might thrive in this role if you have A strong track record building and operating high-scale backend or data-intensive distributed systems in production Excellent systems judgment and the a

P-926 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started in Bengaluru , India ! As a software engineer with a backend focus, you will work with your team to build infrastructure for the Databricks platform at scale. The impact you'll have: Our backend teams cover a diverse range of domains, from core compute fabric resource management to service platforms and infrastructure. For example, you might work on challenges such as: Supporting Databricks' growth by building foundational infrastructure platforms that enable seamless operation across numerous geographic regions and cloud providers. Implementing cloud-agnostic infrastructure abstractions to help Databricks engineers more efficiently manage and operate their services. Develop tools and processes that drive engineering efficiency at Databricks. We enhance the developer experience for Databricks engineers across various areas, including programming languages, linters, static analysis, IDEs, remote development environments, automated release pipelines, and test automation frameworks. Our current focus is on optimizing the Rust development experience across the organization. What we look for: BS (or higher) in Computer Science, or a related field 6+ years of production level experience in one of: Python, Java, Scala, C++, or similar language. Experience developing large-scale distributed systems from scratch Experience working

P-928 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started in Bengaluru , India ! As a software engineer with a backend focus, you will work with your team to build infrastructure for the Databricks platform at scale. The impact you'll have: Our backend teams cover a diverse range of domains, from core compute fabric resource management to service platforms and infrastructure. For example, you might work on challenges such as: Supporting Databricks' growth by building foundational infrastructure platforms that enable seamless operation across numerous geographic regions and cloud providers. Implementing cloud-agnostic infrastructure abstractions to help Databricks engineers more efficiently manage and operate their services. Develop tools and processes that drive engineering efficiency at Databricks. We enhance the developer experience for Databricks engineers across various areas, including programming languages, linters, static analysis, IDEs, remote development environments, automated release pipelines, and test automation frameworks. Our current focus is on optimizing the Rust development experience across the organization. What we look for: BS (or higher) in Computer Science, or a related field 3+ years of production level experience in one of: Python, Java, Scala, C++, or similar language. Experience developing large-scale distributed systems from scratch Experience working