UNKNOWN

FEED

Team members are expected to work from our San Francisco office three full days per week , with the remaining days worked remotely and are expected to be available during agreed working hours and to maintain sufficient overlap with the relevant team’s time zone. Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 30M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands.

YEAR

Higgsfield

Data Engineer

ea_via_bold

FULL_TIME

Built on the Redica Catalyst Platform and powered by Redica ID, Redica unifies the industry's most complete regulatory and inspection datasets, sourced from hundreds of global health authorities, into trusted intelligence for quality and regulatory teams. Manages Complexity: You actively synthesize solutions from complex information by identifying patterns and developing effective problem-solving strategies to solve data-related problems effectively.

REDICA Systems

Senior Data Engineer

SmartRecruiters_Organic_Non_Easy_Apply

We are building the Agent Cloud and power the infrastructure behind AI labs and some of the most widely used consumer and enterprise agents, including Manus, Genspark, Lindy, Groq, and Artificial Analysis. We already generate 8-figure revenue and work directly with top-tier AI companies like Manus, Genspark, Lindy, Groq, Artificial Analysis and other exciting teams pushing the frontier of AI.

The role may focus on subsurface and well data-including seismic interpretation, well logs, drilling and completions, reservoir models, production history, and well performance-as well as data engineering, integration, quality, governance, and analytics across exploration, appraisal, development, and production. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities.

Deloitte Touche Tohmatsu Ltd

Petrotechnical Data Solutions Engineer (Upstream)

linkup_via_bold

We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved - people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. Data Infrastructure Expertise: Possess deep experience designing and building data platforms, including data warehouses, data lakes, streaming systems, and ETL/ELT frameworks.

Crusoe Energy

Senior Software Engineer, Data Platform

Staff Software Engineer, Data Platform

We're looking for a data engineering leader who can own our data platform end to end: You've designed and operated data platforms at scale, with broad hands on experience across the ecosystem distributed processing, lakehouses, warehouses, streaming, orchestration and people usually come to you for technical guidance. Day to day, that looks like: Setting the technical direction for our data platform: evolving our warehouse, data lake, and ETL/ELT architecture to scale with patient and customer growth, and picking the right tools (batch and streaming processing, table formats, orchestration, query engines).

Metriport

Staff Data Engineer

You will work directly on the architecture powering real-time indexing of perception/robotics data, distributed storage/compute, and dataloading at line-rate to GPUs for model training and inference. Practical exposure to scaling cloud infrastructure (AWS S3) and managing heavy-compute data pipelines (bonus points for experience with CUDA, GPU streaming, or video decoding frameworks).

Eventual.Inc

Software Engineer, Data Systems

Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove. *Note: This position requires presence in our San Francisco or San Jose office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

Lambda

Staff Mechanical Engineer - Data Center Cooling

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You'll work closely with analytics, product, and engineering leadership to enable data-driven decision making at scale while building systems that serve millions of users and inform critical business decisions. 10+ years as a data or software engineer with deep expertise in distributed systems, data infrastructure, and high-growth SaaS products at massive scale.

Gamma

Our in-office work policy is designed to keep you connected - with four days a week in the office and Fridays from home for those near one of our offices, plus team and company-wide events depending on location. We each bring an owner's mindset to our work, refusing to be outdone and holding ourselves accountable to meet and exceed the highest bars for our teams, our company, and our members.

Chime Capital, LLC

Senior Software Engineer, Data Engineering

Establish and implement global best practices and design new scalable network solutions Conceptualize, build, and maintain automation and tools to support New Product Introductions, network deployment, release engineering, and operations Design and develop solutions that scale across a variety of hardware platforms of network equipment Lead enhancements of automation for continuous integration, validations, testing infrastructure, release, and configuration management across our global backbone, data center, and edge networks Work closely with our hardware, software, and sourcing teams to develop new networking solutions and influence the future of networking and its associated infrastructure Conduct thorough investigations into complex technical issues across networks, ranging from automated tooling to hardware failures and network issues Develop operational process improvements and implement them in scalable, automated workflows to enhance operational efficiency Help increase operational efficiency between peers and cross-functional teams by identifying roadblocks, designing and delivering automation solutions, and driving change Proactively find gaps that impact multiple teams, come up with the execution plan, drive the project, and influence other teams to reach their goals Participate in an on-call rotation to learn from real-world production challenges and take the lessons to improve current and future generation products Contribute to team growth and development through peer mentorshipBachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience An engineering degree, or a related technical discipline, or equivalent experience 8+ years of relevant experience developing scalable and reliable systems and/or networks Experience in the configuration and maintenance of network devices and NMS systems, or applications such as web servers, load balancers, relational databases, storage systems, and messaging systems Experience in developing and understanding network device configurations for at least one vendor (Juniper, Cisco, Arista, Brocade, etc.) Experience working with network hardware, optics, and fiber connectivity products, including evaluating trade-offs between different hardware architectures Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Ability to leverage AI-assisted workflows to accelerate design population, automate testing, and innovate tooling-measurably improving quality and delivery speed Ability to develop and maintain fiber connectivity solutions using automation tools, ensuring data integrity across design-to-deployment pipelines and streamlining workflows between design systems and infrastructure databases Understanding of Physical Network Infrastructure including rack solution design, inter-rack and intra-rack fiber connectivity design, including automation of design synthesis to design and deliver Physical Design Plans (PDPs) for complex backend and frontend network topologies, including AI/GPU cluster fabrics, ring interconnects, and backbone aggregation layers Ability to collaborate cross-functionally with deployment and operations teams to resolve BOM variances, validate configurations, and deliver production-ready network builds on aggressive timelines Experience coding in higher-level languages (e.g., Python, C++, Go, Rust, etc.). Experience in learning software, frameworks, and APIs Ability to collaborate with NPI teams to drive NPI qualification for new network platforms and optics, applying a principled framework to determine testing depth-from full end-to-end validation to targeted feature qualification Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy review) Experience with network topologies, including scale-out and scale-up fabrics, multi-planar solutions, disaggregated solutions, and their tradeoffs, including high-level and low-level topological and configuration design artifact rendering Experience with routing protocols and routing design, including design synthesis and verification frameworks.

Meta Platforms Inc

Production Network Engineer, Design

Establish and implement global best practices and design new scalable network solutions Conceptualize, build, and maintain automation and tools to support new product introductions, network deployment, release engineering, and operations Design and develop solutions that scale across a variety of hardware platforms of network equipment Lead enhancements of automation for continuous integration, validations, testing infrastructure, release, and configuration management across our global backbone, data center, and edge networks Work closely with our hardware, software, and sourcing teams to develop new networking solutions and influence the future of networking and its associated infrastructure Conduct thorough investigations into complex technical issues across networks, ranging from automated tooling to hardware failures and network issues Develop operational process improvements and implement them in scalable, automated workflows to enhance operational efficiency Help increase operational efficiency between peers and cross-functional teams by identifying roadblocks, designing and delivering automation solutions, and driving change Proactively find gaps that impact multiple teams, come up with the execution plan, drive the project, and influence other teams to reach there Participate in an on-call rotation to learn from real-world production challenges and take the lessons to improve current and future generation products Contribute to team growth and development through peer mentorshipBachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 8+ years of relevant experience in developing scalable and reliable systems and/or networks Experience coding in higher-level languages (e.g., Python, C++, Go, Rust, etc) Experience learning software, frameworks, and APIs Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Experience in configuration and maintenance of network devices and NMS systems, or applications such as web servers, load balancers, relational databases, storage systems and messaging systems Experience developing and understanding network device configuration for at least one vendor (Juniper, Cisco, Arista, Brocade, etc.) Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies 2+ years of experience with networking domain in an operational roleMeta builds technologies that help people connect, find communities, and grow businesses. Networking is at the core of all Meta products and experiences, and we are looking for Network Production Engineers who are interested in solving complex technical challenges in the Backbone, Datacenter, and AI Network domains.

Network Production Engineer, DC Frontier

Establish and implement global best practices and design new, scalable network solutions Conceptualize, build, and maintain automation and tools to support new product introductions, network deployment, release engineering, and operations Design and develop solutions that scale across a variety of hardware platforms of network equipment Lead enhancements of automation for continuous integration, validations, testing infrastructure, release, and configuration management across our global backbone, data center, and edge networks Work closely with our hardware, software, and sourcing teams to develop new networking solutions and influence the future of networking and its associated infrastructure Conduct thorough investigations into complex technical issues across networks, ranging from automated tooling to hardware failures and network issues Develop operational process improvements and implement them in scalable, automated workflows to enhance operational efficiency Help increase operational efficiency between peers and cross-functional teams by identifying roadblocks, designing and delivering automation solutions, and driving change Proactively find gaps that impact multiple teams, come up with the execution plan, drive the project, and influence other teams to reach their goals Participate in an oncall rotation to learn from real-world production challenges and take the lessons to improve current and future generation products Contribute to team growth and development through peer mentorshipBachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience 8+ years of relevant experience in developing scalable and reliable systems and/or networks Experience coding in higher-level languages (e.g., Python, C++, Go, Rust, etc.) Experience learning software, frameworks, and APIs Experience in the configuration and maintenance of network devices and NMS systems, or applications such as web servers, load balancers, relational databases, storage systems, and messaging systems Experience developing and understanding network device configuration for at least one vendor (Juniper, Cisco, Arista, Brocade, etc.) Experience with physical network infrastructure design including rack solutions, fiber connectivity, and automated design synthesis for AI or GPU cluster fabrics, ring interconnects, or backbone aggregation topologies Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Experience with centralized or hybrid routing design, including synthesis and verification frameworks for large-scale multiplanar or disaggregated network topologies Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience integrating AI-assisted workflows or automation tooling to accelerate network design, testing, or operational processes with measurable efficiency or quality improvements Experience qualifying new network hardware platforms and optics through structured NPI frameworks, including end-to-end validation and targeted feature qualificationMeta builds technologies that help people connect, find communities, and grow businesses. Networking is at the core of all Meta products and experiences, and we are looking for Network Production Engineers who are interested in solving complex technical challenges in the backbone, datacenter, and AI network domains.

Production Engineer, Network AI Lead

Establish and implement global best practices and design new scalable network solutions Conceptualize, build, and maintain automation and tools to support new product introductions, network deployment, release engineering, and operations Design and develop solutions that scale across a variety of hardware platforms of network equipment Lead enhancements of automation for continuous integration, validations, testing infrastructure, release, and configuration management across our global backbone, data center, and edge networks Work closely with our hardware, software, and sourcing teams to develop new networking solutions and influence the future of networking and its associated infrastructure Conduct thorough investigations into complex technical issues across networks, ranging from automated tooling to hardware failures and network issues Develop operational process improvements and implement them in scalable, automated workflows to enhance operational efficiency Help increase operational efficiency between peers and cross-functional teams by identifying roadblocks, designing and delivering automation solutions, and driving change Proactively find gaps that impact multiple teams, come up with the execution plan, drive the project, and influence other teams to reach there Participate in an on-call rotation to learn from real-world production challenges and take the lessons to improve current and future generation products Contribute to team growth and development through peer mentorshipBachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 6+ years of experience planning, designing, building, and/or operating scalable and reliable systems and/or networks Experience coding in at least one programming language (e.g., Python, C++, Go, Rust, or Java) and rapidly learning new development languages, software, frameworks, and APIs Demonstrated knowledge of TCP, IPv4/6, Routing Protocols (one or more of BGP, MPLS, ISIS, or similar), and related network services (e.g., DHCP and DNS) Experience developing and understanding network device configuration in multi-vendor environments (Juniper, Cisco, Arista, Brocade, etc.) Experience in configuration and maintenance of network devices and NMS systems, or applications such as web servers, load balancers, relational databases, storage systems, and messaging systems Hardware evaluation and vendor management experience Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Knowledge of IB/RDMA/RoCE Networks, including RDMA congestion control mechanisms, AI training workloads and demands they exert on networks Proven experience designing, developing, and operating distributed systems at scale, with an in-depth understanding of the challenges and opportunities in this space 6+ years of experience building software solutions for managing network infrastructure, with a focus on scalability and reliability Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) In-depth knowledge of software and network debugging, profiling, and instrumentation techniques to ensure optimal system performance Experience designing and maintaining automated testing infrastructure to ensure the quality and reliability of our systems Master's degree or graduate work experience in Computer Science, Computer Engineering, or a related technical fieldMeta builds technologies that help people connect, find communities, and grow businesses. Networking is at the core of all Meta products and experiences, and we are looking for Network Production Engineers who are interested in solving complex technical challenges in the Backbone, Datacenter, and AI Network domains.

Network Production Engineer, Network.AI

Experience in learning software, frameworks, and APIs An engineering degree, or a related technical discipline, or equivalent experience Experience in the configuration and maintenance of network devices and NMS systems, or applications such as web servers, load balancers, relational databases, storage systems, and messaging systems Experience in developing and understanding network device configurations for at least one vendor (Juniper, Cisco, Arista, Brocade, etc.) Strong understanding of network hardware, optics and fiber connectivity products including tradeoffs between different hardware architectures Understanding of Physical Network Infrastructure including rack solution design, inter-rack and intra-rack fiber connectivity design, including automation of design synthesis to design and deliver Physical Design Plans (PDPs) for complex backend and frontend network topologies, including AI/GPU cluster fabrics, ring interconnects, and backbone aggregation layers Ability to collaborate cross-functionally with deployment and operations teams to resolve BOM variances, validate configurations, and deliver production-ready network builds on aggressive timelines Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Ability to develop and maintain fiber connectivity solutions using automation tools, ensuring data integrity across design-to-deployment pipelines and streamlining workflows between design systems and infrastructure databases Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Ability to leverage AI-assisted workflows to accelerate design population, automate testing, and innovate tooling-measurably improving quality and delivery speed Strong understanding of routing protocols and routing design including design synthesis and verification frameworks. Establish and implement global best practices and design new scalable network solutions Conceptualize, build, and maintain automation and tools to support New Product Introductions, network deployment, release engineering, and operations Design and develop solutions that scale across a variety of hardware platforms of network equipment Lead enhancements of automation for continuous integration, validations, testing infrastructure, release, and configuration management across our global backbone, data center, and edge networks Work closely with our hardware, software, and sourcing teams to develop new networking solutions and influence the future of networking and its associated infrastructure Conduct thorough investigations into complex technical issues across networks, ranging from automated tooling to hardware failures and network issues Develop operational process improvements and implement them in scalable, automated workflows to enhance operational efficiency Help increase operational efficiency between peers and cross-functional teams by identifying roadblocks, designing and delivering automation solutions, and driving change Proactively find gaps that impact multiple teams, come up with the execution plan, drive the project, and influence other teams to reach their goals Participate in an on-call rotation to learn from real-world production challenges and take the lessons to improve current and future generation products Contribute to team growth and development through peer mentorshipBachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 8+ years of relevant experience developing scalable and reliable systems and/or networks Experience coding in higher-level languages (e.g., Python, C++, Go, Rust, etc.).

Network Production Engineer, Design

Expert/Master in common families of machine learning models, feature engineering, feature selection techniques, and tuning of machine learning models. MS in Computer Science or Machine Learning with 2+ years of industry experience or PhD in related field with 1+ years of industry experience required.

Happy Elements

Machine Learning Engineer

What you'll do: Design, build, test, and deploy scalable, intelligent data solutions that support millions of Sam’s Club customers—while laying the groundwork for Agentic AI systems that consume and act on this data. Option 3: Master's degree in Computer Science and 1 year’s experience in software engineering or relatedfield.2 years' experience in data engineering, database engineering, business intelligence, or business analytics.

What started small, with a single discount store and the simple idea of selling more for less, has grown over the last 50 years into the largest retailer in the world. Each week, nearly 265 million customers and members visit our more than 11,200 stores under 55 banners in 27 countries and eCommerce websites in 10 countries. With fiscal year 2018 revenue of $500.3 billion, Walmart employs over 2.2 million associates worldwide. Walmart continues to be a leader in sustainability, corporate philanthropy and employment opportunity. It’s all part of our unwavering commitment to creating opportunities and bringing value to customers and communities around the world.

Walmart

ADAPTED_NOW

As Thunderbird evolves beyond a single desktop application, we are expanding across desktop, mobile, paid services, AI offerings, and enterprise-facing work to build independent, privacy-respecting alternatives to big tech ecosystems. Along the way, you’ll provide technical and product direction across teams, mentor other engineers, and identify ways to make our systems and processes more sustainable, scalable, and easier to work with.

Mozilla

Staff Software Engineer, Web Application Services

Ivy Exec

By actively applying intelligence to agent traces and automatically surfacing the most critical patterns, Braintrust gives teams the visibility to understand how agents behave in production and the tools to improve them. Experience with our stack, or close equivalents: Snowflake, dbt, Dagster, AWS Batch/Lambda, Fivetran, Terraform, GitHub Actions, Soda, or semantic-layer tools like Omni or Looker.

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Production Engineer, Network AI Lead Meta Platforms Inc

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