At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions.

The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all.

Job Description 

As a Sr. Research Scientist on the Scaling team, you will be responsible for keeping up with the latest developments in deep learning and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state-of-the-art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible.

The Impact you will have

As a Sr. Research Scientist on the AI Research Team at Databricks, You Will: 

• Define and lead independent research agendas on foundation model efficiency in model training and reinforcement learning, conducting experiments to empirically validate hypotheses and benchmark against state-of-the-art approaches
• Drive algorithmic innovations for large-scale neural network training or inference (e.g., novel optimizers, low-precision techniques, model adaptation methods)
• Optimize ML systems for distributed training, memory efficiency, and compute efficiency through hands-on implementation.

What We Look for

• MS/PhD in Computer Science or related field with strong foundations in machine learning and systems
• Proven ability to write high-quality, efficient code in Python and PyTorch for research implementation and experimentation
• Strong preference for candidates with first-author publications at top ML/systems conferences (ICLR, ICML, NeurIPS, MLSys) focused on optimization or efficiency.

About the Team

The Counter Intrusion MSE team develops systems that provide force protection capabilities, monitoring the perimeter of secure areas, land or sea, for approaching people, vehicles, and vessels. We live in a world where security officers are increasingly overwhelmed by sensor data feeds. Our products leverage advanced sensor fusion and autonomy to seamlessly render activity in the environment to Lattice's common operating picture. This relieves operators of our system from a ton of burden and allows our customers to get more done with fewer personnel. Increasingly, Counter Intrusion MLEs are working on projects to bring customers' existing legacy security systems into the Lattice ecosystem. Key to this effort is building scalable software solutions so that we can service many customers without requiring bespoke software for each one. The Counter Intrusion team is responsible for the development, testing, deployment, and sustainment of our family of systems. We work closely with other teams from product, engineering, sales, logistics, operations, and mission success.

About the Role

We are looking for a Machine Learning Engineer to apply the latest research to solve our toughest problems. This role will be responsible for owning the whole machine learning stack for the Counter Intrusion team. You will design and train multi-sensor object detection models for perception on edge compute devices that push the boundaries of what's possible with our sensors. You will develop learning algorithms to optimize the behavior of autonomous systems. You will also be responsible for the end-to-end design, implementation, and performance of the ML stack, including the infrastructure for data collection and training. Your work will directly impact Anduril's ability to deliver cutting-edge defense technology, with the opportunity to identify and develop novel ML applications across our product portfolio.

Responsibilities

• Propose and prototype innovative solutions to solve real-world problems, leveraging the latest state-of-the-art techniques in the field
• Develop and maintain core ML pipelines
• Train and deploy deep learning models for real-time applications
• Collaborate cross-functionally with camera, systems and labeling teams
• Curate datasets for evaluating performance and comparing performance trends over time
• Provide technical mentorship to other junior ML engineers

Required Qualifications

• MS or PhD in Machine Learning, Robotics or Computer Science, with emphasis on Computer Vision
• BS in Computer Science, Machine Learning, Electrical Engineering, or related field
• 6+ years of experience developing, benchmarking and optimizing ML algorithms on large-scale datasets
• Strong Deep Learning and CV background
• Proficiency in C++ development in a Linux environment
• Experience with Python development and deep learning frameworks such as PyTorch, JAX and TensorFlow
• Experience deploying models with TensorRT and ONNX
• Optimize on-device inference and vision kernels across CPU/GPU/NPU
• Track record of developing and deploying CV models from R&D to production
• Experience writing and maintaining automated continuous integration tests
• Knowledge of system profiling and tuning for latency, memory and power efficiency
• Ability to conduct experiments, ablation studies and create highly detailed reports
• Eligible to obtain and maintain a U.S. Secret security clearance

Preferred Qualifications

• Experience in one or more of the following:
• Object Detection, Object Tracking, Instance Segmentation, Semantic Segmentation, Semantic Change Detection, Depth Estimation, Model Pruning and Compression
• Experience in one or more of the following:
• Visual Odometry, SLAM, Multi-view Geometry, Camera Models, RGB-D and LIDAR Sensor Fusion, Optical Flow
• Experience troubleshooting and analyzing remotely deployed software systems
• 1 year of experience in a technical leadership role

About the Role

We're hiring an AI Engineer to work on the AI core of Mill Commercial — the computer vision and agentic systems that turn a stream of food waste into operational intelligence for commercial kitchens. Mill Commercial integrates a camera and onboard compute directly into our high-capacity food recycler; models running on the edge identify, classify, and quantify food scraps at the point of generation, and our vision pipeline turns that signal into procurement and operational guidance for large food service operators.

You'll join a small AI team, building the data and training pipeline that produces our edge CV models, designing the cloud-side evaluation that tells us whether those models are good enough to ship, and helping build the agentic, LLM-driven product features that turn raw waste data into customer-facing insights and recommendations. This is a hands-on senior IC role for someone who's equally comfortable fine-tuning a segmentation model, prompting a VLM, and wiring an agent into a product feature.

What You'll Do

• Build and manage the end-to-end ML training pipeline: data ingestion from deployed kitchen units, ground truth generation, annotation tooling (including foundation-model-assisted labeling), training, evaluation, and retraining cycles.
• Train and evaluate segmentation, classification, and mass-estimation models for the Mill Commercial camera pipeline — from prompting foundation models to fine-tuning ConvNets and VLMs.
• Build the cloud-side evaluation harness that tells us how our shipped edge models are actually performing in the field — automated, reproducible, and aligned to product accuracy targets across food types, kitchen environments, and deployment configurations.
• Own MLOps: reproducible training, experiment tracking, model versioning, and automated evaluation against product-defined accuracy targets.
• Export and validate models for deployment to edge devices, working closely with the edge team on optimization, quantization, and integration.
• Help design and build the LLM- and agent-powered product features that consume waste characterization data and turn it into customer-facing recommendations — purchasing suggestions, anomaly explanations, operational nudges. Define how agents call tools, ground in customer data, and stay reliable in production.
• Analyze failure cases systematically — unfamiliar food classes, novel kitchen environments, challenging lighting and clutter conditions — and drive the data and modeling decisions that close accuracy gaps.

What We're Looking For

• Strong fundamentals in computer vision and deep learning — segmentation, detection, classification, tracking. You understand the architectures well enough to make informed choices.
• Fluency with modern ML approaches — VLMs, LLMs, foundation models, and agentic systems — alongside classical deep learning. You know when to fine-tune a ConvNet, when to prompt a VLM, and when to wire up an agent, and you understand the practical realities of putting any of them into a product.
• Experience building ML training pipelines and data annotation systems at scale.
• Experience evaluating ML models rigorously — designing metrics, building the eval harness, and using results to drive product decisions rather than just publish a number.
• Proficiency with cloud ML infrastructure (AWS or equivalent) — you've managed training jobs, data pipelines, and experiment workflows in production.
• Familiarity with cloud-to-edge model deployment.
• Clear, direct communication — you can explain tradeoffs to non-technical stakeholders, push back honestly when you disagree, and write docs that others can follow.
• Genuine interest in applying AI to food waste reduction and sustainability. This is a mission-driven product and we want people who care about the mission.

Software skills: Python, PyTorch, OpenCV. Strong familiarity with MLOps on AWS infrastructure. Experience with LLM and agent frameworks. Google Cloud / Gemini experience is a plus.

Nice to Have

• Experience with video understanding (temporal consistency, tracking, video segmentation)
• Experience with foundation models for data annotation
• Experience with MLOps tooling (Weights & Biases, MLflow, SageMaker, or equivalents)
• Experience shipping LLM- or agent-powered features in a consumer or B2B product
• Hardware / IoT product experience, particularly with computer vision and cameras for embedded systems

The estimated base salary range for this position is $240 to $280k, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs. At Mill, it is not typical for an individual to be hired at or near the top of the range for their role.

What We're Looking For

As we continue to expand our footprint, we are looking for a sharp, agile, and business-minded lawyer to join our lean legal team. You will be the primary engine behind our commercial contracting process. This is not a "siloed" role; you will be the cross-functional glue between Finance, Engineering, Sales, and Security, ensuring our legal strategy moves at the speed of our innovation. 

This is an ideal opportunity for a high-performing lawyer with a strong grasp of transactional fundamentals who is ready to "level up." While your primary focus will be owning the commercial contract lifecycle, you will have a front-row seat to the broader legal challenges of a hyper-growth AI company.

You will be joining the Legal Team and report to our VP of Legal. This is a hybrid role based in our San Francisco or New York office with an in-office requirement of 2 days per week.

What You’ll Do

• Lead the drafting and negotiation of a wide variety of contracts, including Master Service Agreements (MSAs), NDAs, Data Processing Addenda (DPAs), and vendor agreements.
• Serve as the legal point of contact for CX, Sales, Engineering, and Finance teams to streamline deal cycles and mitigate risk.
• Navigate complex technology transactions, specifically focusing on intellectual property rights and data privacy frameworks in the context of AI and cloud computing.
• Beyond commercial matters, you will assist the VP of Legal on special projects, potentially spanning corporate governance, employment, and regulatory compliance as the company scales.

What You’ll Need

• 3–5 years of legal practice, with a focus on commercial or corporate transactions.
• A proven track record at a top-tier law firm, in-house at a high-growth tech company, or a strategic mix of both.
• A deep understanding of technology transactions, including the nuances of IP licensing and data privacy provisions.
• You are a confident negotiator who knows when to hold the line and when to find a creative solution to get the deal done.

Compensation

What We’re Looking For

We are looking for a Senior Finance Associate to drive priorities across strategic finance, corporate development, and FP&A as Lightning AI scales. You will partner with cross-functional stakeholders to shape unit economics, advise on deal pricing, and guide investment decisions. You will support GPU financing, fundraising, and investor relations to help Lightning AI acquire and allocate capital effectively. You will also build an operating cadence for P&L management, reporting, forecasting, and planning, turning data into decision-ready insights for leadership. 

The finance scope is deep, leadership visibility is high, and the work directly influences revenue growth, margin expansion, and capital allocation. If you want meaningful ownership, steep learning, and proximity to the decisions that shape an AI cloud, this role is for you.

This is a hybrid role based in our San Francisco or New York office with an in-office requirement of 2 days per week.

What You’ll Do

• Support deal reviews with Sales and leadership and recommend pricing decisions
• Partner with Marketing on spend allocation, pipeline efficiency, and unit economics analyses (LTV/CAC, payback period)
• Partner with Product on ROI for software investments and strategic initiatives
• Partner with Infrastructure Operations on capacity planning and CapEx assessment
• Model GPU financing structures and assess returns
• Support lender and investor communications, materials, and data rooms
• Monitor industry trends and the competitive landscape to identify potential business risks and opportunities
• Contribute to M&A sourcing and diligence models
• Build and maintain a driver based model for P&L, balance sheet, and cash flow statement
• Prepare executive-level business reviews for leadership and board
• Lead monthly and quarterly reporting, ensuring accuracy and highlighting key business drivers
• Develop forecast cycles and strengthen forecast accuracy by partnering closely with cross-functional stakeholders
• Support annual planning and long-range planning 
• Conduct rigorous analysis of key performance indicators, operational metrics, and business trends
• Manage FP&A systems and tooling and maintain data accuracy

What You’ll Need

• Bachelor's degree in Business Administration, Finance, Economics, or a related field
• 4+ years in Strategic Finance, FP&A, investment banking, private equity, or venture capital, ideally with a focus on software, AI, and/or cloud infrastructure
• Advanced proficiency in Excel and Google Sheets and experience building complex financial models
• Excellent written and verbal communication
• Track record of cross-functional partnership
• Analytical and strong problem-solving ability
• Team player with a growth mindset, positive attitude, and strong work ethic
• Bias to action and desire to work in a startup environment
• Experience with capital markets, M&A, or CapEx financing
• Exposure to cloud or AI infrastructure economics and data center capacity planning
• Familiarity with FP&A systems and data tooling (e.g., NetSuite)

Compensation

What We're Looking For

As a Machine Learning Solutions Engineer, you will operate at the intersection of machine learning, distributed systems, and cloud infrastructure.
You will partner with customers to design and deploy end-to-end AI systems, spanning:

• Model development and training
• GPU infrastructure and cluster design
• Distributed inference and production deployment

This role goes beyond traditional ML solutions engineering—you will act as a technical architect, helping customers make critical decisions across compute, orchestration, and system design.

The role can be based out of our New York City or San Francisco office, with an in-office requirement of at least 2-3 days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this role at this time. The annual base pay range for this role is $150,000 - $195,000, in addition to a variable pay component and meaningful equity. 

What You’ll Do

Customer Architecture & Technical Leadership

• Partner with customers to understand ML workloads, infrastructure constraints, and scaling requirements
  
  
• Architect end-to-end solutions across:
  
  
• Data pipelines (CPU → GPU workflows)
  
  
• Distributed training (multi-node, multi-GPU)
  
  
• High-throughput inference systems
  
  
• Translate business goals (latency, cost, throughput) into technical system design decisions
  
  

GPU & Infrastructure Design

• Design and optimize workloads across GPU clusters (H100, H200, B200, etc.)
  
  
• Advise on:
  
  
• Training vs inference cluster design
  
  
• Interconnect choices (Ethernet vs Infiniband / RDMA vs Roce)
  
  
• Storage strategies (local NVMe vs networked / object storage)
  
  
• Model and optimize for:
  
  
• Tokens/sec, tokens/$
  
  
• Throughput vs latency tradeoffs
  
  
• GPU utilization and scheduling efficiency
  
  

Kubernetes & Platform Systems

• Design and support deployments on Kubernetes (EKS, GKE, on-prem clusters)
  
  
• Work with:
  
  
• GPU scheduling (time-slicing, MIG, bin-packing)
  
  
• Autoscaling and workload orchestration
  
  
• Helm-based deployments and multi-tenant environments
  
  
• Help customers balance:
  
  
• Raw Kubernetes flexibility vs platform abstraction (Lightning)
  
  

Demos, POCs, and Execution

• Build and deliver technical demos and POCs that showcase:
  
  
• Distributed training workflows
  
  
• Scalable inference endpoints
  
  
• End-to-end ML pipelines on Lightning AI
  
  
• Scope and lead POCs aligned to customer success metrics (latency, cost, reliability)
  
  

Cross-Functional Impact

• Act as the bridge between customers, product, and engineering
  
  
• Provide feedback on:
  
  
• Platform gaps in infrastructure, orchestration, and performance
  
  
• Emerging patterns in GPU usage and distributed systems
  
  
• Influence roadmap across ML workflows and infrastructure capabilities
  
  

Enablement & Thought Leadership

• Create technical content
• Architecture guides (e.g., high-throughput LLM inference systems)
• Best practices for GPU utilization and scaling
• Educate customers on modern AI infrastructure patterns

What You’ll Need

ML + Systems Expertise

• 3–6+ years experience in:
  
  
• Machine Learning / AI Engineering
  
  
• Solutions Engineering / Sales Engineering / ML Consulting
  
  
• Strong understanding of:
  
  
• Training vs inference workloads
  
  
• Model optimization (quantization, batching, caching, etc.)
  
  

GPU & Distributed Systems

• Experience working with:
  
  
• GPU clusters (NVIDIA stack preferred)
  
  
• Distributed training or inference systems
  
  
• Familiarity with:
  
  
• NCCL, CUDA, or GPU performance profiling
  
  
• Networking concepts (RDMA, Roce, Infiniband, high-throughput systems)
  
  

Kubernetes & Cloud Platforms

• Hands-on experience with:
  
  
• Kubernetes (EKS, GKE, or on-prem)
• Slurm 
• Containerization (Docker)
  
  
• Exposure to:
  
  
• GPU scheduling in Kubernetes environments
  
  
• Multi-tenant or production ML deployments
  
  

Programming & Tooling

• Strong Python skills (PyTorch preferred)
  
  
• Experience building:
  
  
• ML pipelines
  
  
• APIs or inference services
  
  
• Familiarity with Lightning AI, PyTorch Lightning, or similar frameworks is a plus
  
  

Customer-Facing Excellence

• • Ability to:
    
    
    • Explain complex infrastructure and ML tradeoffs clearly
      
      
    • Run technical discovery and uncover quantifiable success metrics
      
      
  • Experience working cross-functionally with:
    
    
    • Sales, product, and engineering teams

What We're Looking For

Lightning AI is seeking a Senior Storage Infrastructure Engineer to join our Infrastructure Engineering team.

In this role, you will focus on building and operating the storage systems that power large-scale AI/ML training, inference, and HPC workloads. You will work at the intersection of software, hardware, and operations—developing automation, improving reliability, and scaling distributed storage systems across our bare-metal infrastructure.

You will help own the data plane of our storage infrastructure, supporting high-throughput, low-latency data access for some of the most demanding AI workloads. You’ll play a key role in managing and evolving our storage stack (including VAST and S3-compatible systems like Ceph), ensuring performance, reliability, and efficiency at scale.

We’re flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time.

What You'll Do

Storage Systems & Infrastructure

• Operate and scale distributed storage systems, including VAST and S3-compatible object storage (e.g., Ceph)
• Improve performance, reliability, and efficiency of storage systems supporting large-scale AI/ML workloads
• Troubleshoot complex storage and data path issues across hardware and software layers
• Optimize storage performance to support high-throughput, low-latency AI training and inference workloads

Automation & Tooling

• Build and maintain automation for provisioning, managing, and monitoring storage infrastructure
• Develop Python-based tools and workflows to reduce manual operational overhead
• Improve lifecycle management of storage clusters, from deployment through maintenance and scaling

Systems & Operations

• Manage and operate Linux-based systems in production, including bare-metal environments
• Partner with infrastructure and data center teams on hardware bring-up, upgrades, and issue resolution
• Support capacity planning, utilization tracking, and forecasting for storage systems
• Leverage monitoring and telemetry to diagnose issues and improve system performance and reliability

Cross-Functional Collaboration

• Work closely with Infrastructure Engineering, Network Engineering, and Platform teams to integrate storage into the broader platform
• Contribute to design discussions around new infrastructure deployments and scaling strategies
• Help define best practices for operating storage systems in high-performance computing environments

What You'll Need

Required Qualifications

• 5+ years of experience in infrastructure engineering, systems engineering, or related roles
• Hands-on experience operating distributed storage systems (e.g., VAST, Ceph, or similar)
• Strong Linux systems experience in production environments
• Proficiency in Python or similar scripting/programming languages for automation
• Experience working with bare-metal infrastructure and hardware-oriented systems
• Ability to debug complex issues across system boundaries (storage, OS, hardware, networking)
• Experience with storage networking protocols (e.g., NFS or similar)
• Experience with capacity planning, monitoring, and performance tuning

Ideal Experience

• Experience with VAST storage systems in production environments
• Experience operating S3-compatible object storage at scale
• Data center operations experience, including working with physical hardware
• Familiarity with AI/ML or HPC workloads and their storage requirements
• Background in high-performance or low-latency distributed systems
• Familiarity with high-performance data transfer technologies (e.g., RDMA, GPU Direct Storage)
• Experience supporting GPU-based workloads or large-scale compute clusters

Compensation

What We’re Looking For

Lightning AI is seeking an Observability Infrastructure Engineer to join our Infrastructure Engineering team.

In this role, you will own and evolve observability systems across large-scale, GPU-enabled bare-metal infrastructure. You’ll operate at the intersection of infrastructure, data, and product, building platforms for metrics, logs, traces, and alerting that power both internal operations and customer-facing visibility.

You will play a key role in productizing observability, enabling scalable, multi-tenant monitoring experiences while keeping pace with rapid infrastructure buildouts. This includes designing telemetry pipelines, improving signal quality, and delivering actionable insights that ensure reliability and transparency across our platform.

We’re flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

Observability Platform & Productization

• Own and evolve a scalable observability platform spanning metrics, logs, traces, and events
• Drive the productization of observability capabilities for both internal teams and external customers
• Design multi-tenant observability systems with scoped access, RBAC, and customer-facing visibility
• Continuously improve observability systems to keep pace with rapid infrastructure buildouts

Telemetry & Data Pipelines

• Design and operate telemetry pipelines ingesting data from GPUs, CPUs, networking (Ethernet & InfiniBand), containers, APIs, and BMC/Redfish
• Build systems to correlate signals across infrastructure layers to enable faster debugging and root cause analysis
• Implement streaming and real-time data pipelines using tools such as Kafka, OTEL, Promtail, or similar

Alerting, Reliability & Insights

• Design and implement noise-resistant alerting systems to improve signal quality and reduce operational load
• Create dashboards and alerting for InfraOps, Engineering, and Customer Success teams
• Build automated insights and enable proactive detection, forecasting, and system health visibility at scale

Systems & Infrastructure Engineering

• Contribute to broader infrastructure engineering projects beyond observability
• Partner with infrastructure and platform teams to embed observability into core systems and workflows
• Support large-scale, distributed systems across compute, networking, and storage environments

Cross-Functional Collaboration

• Work closely with customer-facing teams to deliver external observability experiences
• Collaborate with engineering, operations, and support teams to improve system transparency and reliability
• Help define best practices for observability across the organization

What You’ll Need

Required Qualifications

• 5+ years of experience in infrastructure engineering, SRE, or observability-focused roles
• Strong experience with monitoring systems such as Prometheus, Grafana, ELK, or VictoriaMetrics
• Experience building and operating observability platforms at scale
• Proficiency in Python, Go, or bash for automation and data integration
• Familiarity with containerized environments and Kubernetes observability
• Experience with streaming telemetry pipelines (Kafka, OTEL, Promtail, or equivalent)
• Experience with multi-tenant monitoring architectures
• Strong written and verbal communication skills

Ideal Experience

• Experience with GPU observability, particularly NVIDIA DCGM
• Experience monitoring large-scale GPU or HPC clusters
• Familiarity with InfiniBand fabric observability
• Experience building customer-facing or productized infrastructure systems
• Experience with correlation engines, RCA workflows, or predictive alerting systems
• Broad exposure to infrastructure domains including networking, storage, and provisioning

Compensation

What We're Looking For

Lightning AI is seeking a GPU & Compute Infrastructure Engineer to join our Infrastructure Engineering team.

In this role, you will own image management, system diagnostics, and validation across large-scale bare-metal compute infrastructure, with a particular focus on GPU-enabled systems. You will work at the intersection of hardware, systems, and software—developing automation, improving reliability, and enabling efficient cluster bring-up for AI/ML and HPC workloads.

You will play a key role in owning and evolving our image pipeline, running validation environments and test clusters, and supporting both system-level and GPU hardware qualification. This role is critical to ensuring that our infrastructure is consistent, performant, and ready to support demanding AI workloads from day one.

We’re flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time.

What You'll Do

Systems, Image & Validation Infrastructure

• Own and evolve systems for image management, deployment, and validation across bare-metal infrastructure
• Run and maintain test clusters used for system validation, diagnostics, and bring-up
• Validate firmware, drivers, and OS images across compute and GPU-enabled systems
• Support hardware qualification efforts for next-generation platforms

GPU Diagnostics & Performance

• Own GPU diagnostics and validation workflows across large-scale infrastructure
• Diagnose and resolve complex issues across GPUs, drivers, OS, and hardware layers
• Analyze system and GPU performance using tools such as NVIDIA DCGM
• Identify failure patterns and drive improvements in system stability and validation coverage

Automation & Tooling

• Build and maintain automation for provisioning, validation, and system bring-up
• Develop Python-based tools and workflows to improve efficiency and reduce manual operational overhead
• Improve the reliability, repeatability, and scalability of image pipelines and validation systems

Systems & Operations

• Manage and operate Linux-based systems in production and validation environments
• Manage virtualization technology
• Support bare-metal provisioning workflows, including PXE and image-based systems
• Interface with hardware management systems (e.g., IPMI, Redfish) for monitoring and debugging

Cross-Functional Collaboration

• Partner with Infrastructure, Hardware, and Data Center teams on system bring-up and validation
• Collaborate with platform and ML teams to ensure systems meet workload requirements
• Contribute to best practices for provisioning, diagnostics, and lifecycle management of infrastructure

What You'll Need

Required Qualifications

• 5+ years of experience in infrastructure engineering, systems engineering, or related roles
• Strong Linux systems experience in production environments
• Hands-on experience with GPU-enabled systems and tools such as NVIDIA DCGM
• Familiarity with bare-metal provisioning and system bring-up workflows
• Proficiency in Python or similar scripting/programming languages for automation
• Ability to debug complex issues across hardware, OS, GPUs, and system software

Ideal Experience

• Experience with high-performance interconnects (e.g., InfiniBand, NVLink)
• Experience with PXE boot environments, LiveCD systems, or image-based provisioning workflows
• Experience with hardware management interfaces such as iDRAC, IPMI, or Redfish
• Data center operations experience, including working with physical hardware
• Experience supporting AI/ML or HPC workloads at scale
• Experience with GPU validation frameworks or large-scale hardware qualification processes

Compensation

What We're Looking For

We’re looking for a Fullstack Engineer to help develop and scale the Lightning AI platform across the frontend, CLI, APIs, and core backend systems. In this role, you’ll take ownership of key features and drive them end-to-end, working closely with engineering, product, and design to ship high-quality, iterative improvements. This is an opportunity to build systems that support real-world machine learning workloads at scale.

This role is based in one of our hubs (NYC, SF, Seattle, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

• Write readable/testable/efficient code in React and either Python or Go (Golang).
• Build deep expertise in our technology stack to deliver new features, improve system stability, and increase overall performance.
• Partner with engineering and product leaders on developing the Lightning product while using your experience to set the technical direction for large projects.
• Evaluate, strengthen, and document technical architecture, tools, and processes.
• Maintain high standards for software quality, implement automation, drive continuous delivery, and reduce time to production while proactively reducing technical debt.
• Mentor and coach engineers on system design, operating in high uncertainty, and problem-solving to create a supportive, inclusive environment where each engineer can grow.

What You’ll Need

• Proficiency in React and either Go (Golang) or Python, with a preference for Go
• Strong understanding of software engineering principles and lifecycle
• Hands-on experience as a Fullstack Engineer in a SaaS technology company
• Proven ability to take ownership of key features and drive end-to-end development
• Communication and collaboration with engineers, product managers, and designers
• Ability to operate in high uncertainty and rapidly changing environments

Compensation

What We're Looking For

We’re looking for a Frontend Engineer to help develop and scale the UI and frontend infrastructure of the Lightning AI platform. In this role, you’ll take ownership of key features and drive them end-to-end, working closely with engineering, product, and design to ship high-quality, iterative improvements. With over 10,000 organizations building with Lightning, you’ll have a unique opportunity to impact how the world builds and deploys AI to production.

This role is based in one of our hubs (Seattle, NYC, SF, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

• Write readable/testable/efficient code in React and Redux, and build deep expertise in our technology stack to deliver new features, improve system stability, and increase overall performance.
• Partner with engineering and product leaders on developing the user interface and frontend infrastructure while using your experience to set the technical direction for large projects.
• Evaluate, strengthen, and document technical architecture, tools, and processes.
• Maintain high standards for software quality, implement automation, drive continuous delivery, and reduce time to production while proactively reducing technical debt.
• Mentor and coach engineers on system design, operating in high uncertainty, and problem-solving to create a supportive, inclusive environment in which each engineer can grow.

What You’ll Need

• Proficiency in React, JavaScript and TypeScript.
• Strong understanding of software engineering principles and lifecycle.
• Hands-on experience as a Frontend Engineer in a SaaS technology company.
• Proven ability to take ownership of key features and drive end-to-end development.
• Communication and collaboration with engineers, product managers, and designers.
• Ability to operate in high uncertainty and rapidly changing environments.

Compensation

What We're Looking For

We’re looking for a Backend Engineer to help develop and scale the Lightning AI platform, spanning APIs, infrastructure, billing, security, and integrations. In this role, you’ll take ownership of key features and drive them end-to-end, working closely with engineering, product, and design to ship high-quality, iterative improvements. This is an opportunity to build systems that support real-world machine learning workloads at scale.

This role is based in one of our hubs (Seattle, NYC, SF, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

• Write readable/testable/efficient code in Go (Golang).
• Build deep expertise in our technology stack to deliver new features, improve system stability, and increase overall performance.
• Partner with engineering and product leaders on developing the Lightning product while using your experience to set the technical direction for large projects.
• Evaluate, strengthen, and document technical architecture, tools, and processes.
• Maintain software quality, implement automation, drive continuous delivery, and reduce time to production while proactively reducing technical debt.
• Mentor and coach engineers on system design, operating in high uncertainty, and problem-solving to create a supportive, inclusive environment where each engineer can grow.

What You’ll Need

• Extensive experience writing efficient, maintainable code in Go. Familiarity with best practices in testing, readability, and optimization is essential.
• Broad knowledge of backend and frontend systems, with experience building and scaling APIs, CLI tools, billing systems, and security protocols. Exposure to frontend frameworks is a plus.
• Experience with cloud platforms like AWS, GCP, or Azure and designing systems that are reliable, performant, and scalable. Familiarity with containerization (Docker, Kubernetes) is a strong advantage.
• Proven ability to take ownership of key features and drive end-to-end development
• Commitment to software quality, test automation, and continuous delivery. Experience proactively managing technical debt and speeding up time to production.
• Hands-on experience as a backend or product engineer in a SaaS technology company
• Communication and collaboration with engineers, product managers, and designers
• Ability to operate in high uncertainty and rapidly changing environments

Compensation

The AGI (Artificial General Intelligence) Computing Lab is dedicated to solving the complex system-level challenges posed by the growing demands of future AI/ML workloads. Our team is committed to designing and developing scalable platforms that can effectively handle the computational and memory requirements of these workloads while minimizing energy consumption and maximizing performance. To achieve this goal, we collaborate closely with both hardware and software engineers to identify and address the unique challenges posed by AI/ML workloads and to explore new computing abstractions that can provide a better balance between the hardware and software components of our systems. Additionally, we continuously conduct research and development in emerging technologies and trends across memory, computing, interconnect, and AI/ML, ensuring that our platforms are always equipped to handle the most demanding workloads of the future. By working together as a dedicated and passionate team, we aim to revolutionize the way AI/ML applications are deployed and executed, ultimately contributing to the advancement of AGI in an affordable and sustainable manner. Join us in our passion to shape the future of computing!

Location:  Daily onsite presence at our San Jose, CA office / U.S. headquarters in alignment with our Flexible Work policy.

What You’ll Do

• Develop and maintain highly interactive, large-scale and complex web-based visual analytics tools on AI/ML workloads.
• Design and implement creative and performant visualizations to assist in diagnosing issues or uncovering optimization opportunities in AI/ML inference and serving.
• Collaborate closely with hardware architects and compiler engineers to define, design, and implement effective visualization solutions enhancing their workflow.
• Develop high-performance visualization workflows by integrating independent graphics modules with micro-services to handle asset optimization, ensuring a non-blocking experience on the client.
• Continuously seek improvements to existing tools and develop new approaches to meet fast-evolving requirements.
• Stay up-to-date with the latest advancements in web development and visualization techniques.
• Contribute to the development of the documentation and user guides.
• Complete other responsibilities as assigned.

What You Bring

• Bachelor’s with 10+ years, or Master’s with 8+ years, or PhD's with 5+ years of industry experience.
• An innate drive to clarify deep technical complexity, balancing creative visualization with engineering rigor to build analytical tools that make interdependent hardware and software models intuitive without sacrificing logical precision.
• Strong experience in full-stack visual analytics software development, with a focus on building scientific or infrastructure visualization tools. Experience in AI model visualization integrated with PyTorch is a plus.

• Strong proficiency in modern frontend technologies like React and backend technologies like Node.js or Python-based frameworks. Experience in graph-based UI is a plus.
• Proven experience in WebGL/WebGPU based frameworks such as three.js or deck.gl. GLSL experience is a plus. Experience in WebAssembly with C++ is a plus.
• Excellent problem-solving skills and ability to think critically and creatively.

• Excellent communication and interpersonal skills.
• Ability to work independently and as part of a team.
• You’re inclusive, adapting your style to the situation and diverse global norms of our people.
• An avid learner, you approach challenges with curiosity and resilience, seeking data to help build understanding.
• You’re collaborative, building relationships, humbly offering support and openly welcoming approaches.
• Innovative and creative, you proactively explore new ideas and adapt quickly to change.

#LI-VL1

Snapshot 

At Google DeepMind, our research team is dedicated to tackling the most complex challenges in online information quality. We strive to advance the state of the art by developing innovative solutions to detect manipulated media and misleading narratives, ensuring the integrity of digital discourse. A prominent example of our scientific discovery is Backstory. Our interdisciplinary work spans provenance analysis and the creation of tools for AI-assisted information literacy, leveraging our technologies for the widespread public benefit of a safer online environment. We thrive in a supportive environment that encourages rapid prototyping and iteration, driving our research achievements directly into Google’s flagship models, including Gemini.

About us 

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

We’re a dedicated scientific community, committed to “solving intelligence” and ensuring our technology is used for widespread public benefit. 

We’ve built a supportive and inclusive environment where collaboration is encouraged and learning is shared freely. We don’t set limits based on what others think is possible or impossible. We drive ourselves and inspire each other to push boundaries and achieve ambitious goals.

The role

To succeed in this role, you will need to be passionate about advancing information literacy using machine learning and other computational techniques. You'll join an interdisciplinary team of domain experts, ML researchers, and engineers to research and build multimodal reasoning systems and Vision-Language Models (VLMs) to assess the trustworthiness of media (images, audio, and videos) on the internet.   

Key responsibilities:

• Plan and perform rapid prototyping of computer vision and multimodal machine learning techniques applied to determining authenticity of media information.
• Design and train multimodal models capable of complex visual reasoning.
• Undertake exploratory analysis to inform experimentation and research directions.
• Engage with product teams to drive the development of our research.
• Implement tools, libraries, and frameworks to speed up and enable new research.
• Report and present research findings, software developments, experimental results, and data analysis clearly and efficiently.
• Collaborate with internal and external scientific domain experts.

About you

In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:

• PhD/Master’s degree in Computer Science, AI, ML, or equivalent practical experience.
• At least 2 years of relevant experience developing computer vision techniques or multimodal machine learning models.
• Experience in software development using Python and deep learning frameworks (e.g., Jax, TensorFlow, PyTorch), with a proven track record of building high-quality research prototypes and systems.
• Quantitative skills in math and statistics.
• Experience exploring, analysing and visualising data.

In addition, the following would be an advantage: 

• Experience in training and deployment of large-scale models.
• Experience with Video Understanding
• Experience with Large Language Models, prompt engineering, few-shot learning, post-training techniques, and evaluations.
• A proven track record of research or engineering achievements, such as publications in peer-reviewed conferences or journals.

When assessing technical background we will take a holistic view of the mix of scientific, ML and computational experience. We do not expect you to be an expert in all fields simultaneously.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

The US base salary range for this full-time position is between 174,000 USD - 252,000 USD + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

What We're Looking For

We are looking for an Account Executive with experience selling highly technical, developer-focused products to CTOs, VPs of Engineering, software engineers, researchers, and/or data scientists. You thrive in a fast-paced, start-up environment focusing on every step of the sales process, from prospecting, qualifying, and nurturing leads to running demos, negotiating contracts, and closing deals. We want someone who thinks about how to uncover and address our customers’ problems to drive customer acquisition while feeding their requirements back to inform the product roadmap.

This role is based out of our New York City office, with an in-office requirement of at least 3 days per week and occasional team and company offsites.

What You’ll Do

• Build an understanding of our target markets, value proposition, and pricing models to not only meet but exceed quarterly revenue targets.
• Focus on high-quality, consistent outbound prospecting across key market segments to build the sales pipeline and optimize the customer funnel.
• Qualify and develop both inbound and outbound sales leads.
• Collaborate with the product, engineering, and marketing teams to continuously improve and iterate on the sales process.
• Analyze industry trends and customer segmentation to identify and capitalize on new sources of qualified leads.
• Work alongside the marketing team to increase the number and quality of inbound leads.
• Champion data integrity and accuracy using HubSpot to track activity and manage sales opportunities through the funnel.

What You’ll need

• 5+ years of experience as an Account Executive or in a similar sales role, selling technical or developer-focused products to technical audiences.
• Familiarity with the machine learning, AI, or software development ecosystem, and an ability to grasp complex technical concepts.
• Proven track record of meeting or exceeding revenue targets in a fast-paced startup environment.
• Experience with outbound prospecting, qualifying leads, running demos, and closing deals is essential.
• Ability to uncover customer pain points, articulate value propositions, and effectively address objections to drive solutions.
• Strong interpersonal skills to work cross-functionally with leadership, product, engineering, and marketing teams.
• Proficiency with HubSpot or a similar CRM to track activity, manage the sales pipeline, and ensure data integrity.
• Solid understanding and application of a sales methodology (e.g., MEDDIC, Challenger, or Sandler) with the ability to tailor approaches to different customer needs and scenarios.

Compensation

This role offers $300K OTE, with a 50/50 base/variable split, in addition to meaningful equity. 

Job Title: Principal Engineer, AI System Architect (Hardware)

The Architecture Research Lab (ARL) focuses on addressing fundamental system-level bottlenecks in modern AI, particularly in memory capacity/bandwidth and system-scale communication. By leveraging Samsung’s world-class memory technologies, ARL explores and defines next-generation AI system architectures that deliver step-function improvements in performance, efficiency, and scalability.
We are seeking a Principal AI System Architect who will play a Technical Lead role in bridging AI workloads, system architecture, and hardware design. In this role, you will develop system-level performance models, drive architecture-level design decisions, and propose forward-looking AI system architectures that shape Samsung’s long-term AI platform strategy.

Location: Daily onsite presence at our San Jose office in alignment with our Flexible Work policy

Job ID: 42852

What You’ll Do

• Technically Lead the architecture team with strong  direction, shaping system‑architecture strategy and advancing key innovations
• Conduct system-level architectural research for next-generation AI systems, spanning compute, memory, and interconnect/network subsystems.
• Develop and maintain analytical and simulation-based system modeling frameworks to evaluate AI workloads and identify performance, scalability, and efficiency bottlenecks at rack- and system-scale. 
• Analyze representative and emerging system-level architectural research (e.g., LLMs, DLRMs, and future AI models) to derive architecture requirements and trade-offs across compute, memory, networking, and power.  
• Drive architecture-level design decisions through quantitative modeling, design-space exploration, and performance/power projections. 
• Perform comparative studies of alternative system architectures, reporting performance and performance-per-watt metrics to guide strategic technology choices. 
• Collaborate closely with cross-functional teams in hardware architecture, memory, interconnect, and system engineering to align modeling insights with implementation realities.  
• Communicate architectural insights and recommendations through clear technical presentations and documentation.   
• Occasional domestic and international travel (<10%).

 What You Bring

• Ph.D. in Computer Science, Electrical Engineering, or a related field preferred,  with 15+ years of experience in system architecture for large-scale computing platforms, with a strong focus on AI workloads 
• Proven hands-on experience developing analytical and event-driven simulation models for system-level performance evaluation. 
• Deep understanding of AI system hardware architectures, including compute, memory hierarchies, and high-performance interconnects.
• Strong knowledge of modern and emerging AI workloads, including LLMs, DLRMs, and large-scale training and inference systems.
• Demonstrated ability to translate workload characteristics and modeling results into actionable architectural design decisions.
• Proficiency in Python, C++, and PyTorch for modeling, analysis, and experimentation. 
• Excellent written, verbal, and presentation communication skills, with the ability to influence technical direction across teams.
• A collaborative mindset, intellectual curiosity, and resilience in tackling complex, open-ended system-level challenges. 
• You’re inclusive, adapting your style to the situation and diverse global norms of our people. 
• You approach challenges with curiosity and resilience, seeking data to help build understanding.
• You’re collaborative, building relationships, humbly offering support and openly welcoming approaches.
• Innovative and creative, you proactively explore new ideas and adapt quickly to change.

#LI-SF1

Job Title: Principal engineer, AI Serving Framework Architect (Software)

What You’ll Do    

The Architecture Research Lab (ARL) focuses on addressing fundamental system-level bottlenecks in modern AI, particularly in memory capacity/bandwidth and system-scale communication. By leveraging Samsung’s world-class memory technologies, ARL explores and defines next-generation AI system architectures that deliver step-function improvements in performance, efficiency, and scalability.
We are seeking a Principal AI System Architect who will play a key role in bridging AI workloads, system architecture, and hardware design. In this role, you will develop system-level performance models, drive architecture-level design decisions, and propose forward-looking AI system architectures that shape Samsung’s long-term AI platform strategy.

Location: Daily onsite presence at our San Jose office in alignment with our Flexible Work policy

Job ID: 42853

• As a Tech Lead, leading research teams in Korea and proposing technical direction
• Research on dynamic scheduling methodologies for maximizing AI inference performance in multi-rack scale memory-centric systems, comprised of heterogeneous compute-capable memory and hierarchical memory
• Investigating methods to accelerate search operations in RAG’s vector DB and AI Agent’s knowledge-graph by leveraging compute-capable memory
• Studying strategies for optimally placing KVCache and a vector DB in hierarchical memory to minimize frequent SSD accesses and reduce IO stalls
• Proposing SW design for implementing the derived optimization algorithms on open-source platforms such as vLLM

What You Bring

• PhD in Computer Science or a related field with 10+ years of experience in AI Serving Framework for large-scale computing, with focusing on the AI workloads. 
• Led a project to build and optimize a Large Language Model (LLM) Inference Software Stack on a multi-rack scale system to deliver AI Inference services to over 100,000 users. 
• Extensive experience in designing AI Inference Software Stacks for heterogeneous devices.In-depth understanding of the internal architecture and operation mechanisms of inference engines such as vLLM. 
• Proficiency in AI Inference System Profiling and optimization. 
• Knowledge and practical experience with future AI workloads, including reasoning models, multi-modal solutions, AI agents, and world models. 
• Strong understanding of compute, memory, and networking bottlenecks in AI systems. 
• Required skillsets: PyTorch, Python, and C++ 
• A collaborative mindset, curiosity, and resilience in solving complex challenges. 
• Excellent verbal, presentation, and written communication skills. 
• (Nice to have) Native or fluent Korean speakers are preferred. 
• You’re inclusive, adapting your style to the situation and diverse global norms of our people. 
• You approach challenges with curiosity and resilience, seeking data to help build. Understanding.
• You’re collaborative, building relationships, humbly offering support and openly welcoming approaches. 
• Innovative and creative, you proactively explore new ideas and adapt quickly to change 

#LI-SF1

Job Title: Staff Engineer, AI System Architect (Hardware)

What You’ll Do
The Architecture Research Lab (ARL) focuses on addressing fundamental system-level bottlenecks in modern AI, particularly in memory capacity/bandwidth and system-scale communication. By leveraging Samsung’s world-class memory technologies, ARL explores and defines next-generation AI system architectures that deliver step-function improvements in performance, efficiency, and scalability.
We are seeking a Senior Staff AI System Architect who will play a key role in bridging AI workloads, system architecture, and hardware design. In this role, you will develop system-level performance models, drive architecture-level design decisions, and propose forward-looking AI system architectures that shape Samsung’s long-term AI platform strategy.

Location: Daily onsite presence at our San Jose office in alignment with our Flexible Work policy

Job ID: 42917

• Conduct system-level architectural research for next-generation AI systems, spanning compute, memory, and interconnect/network subsystems.
  • Develop and maintain analytical and simulation-based system modeling frameworks to evaluate AI workloads and identify performance, scalability, and efficiency bottlenecks at rack- and system-scale.
  • Analyze representative and emerging AI workloads (e.g., LLMs, DLRMs, and future AI models) to derive architecture requirements and trade-offs across compute, memory, networking, and power.
  • Drive architecture-level design decisions through quantitative modeling, design-space exploration, and performance/power projections.
  • Perform comparative studies of alternative system architectures, reporting performance and performance-per-watt metrics to guide strategic technology choices.
  • Collaborate closely with cross-functional teams in hardware architecture, memory, interconnect, and system engineering to align modeling insights with implementation realities.
  • Communicate architectural insights and recommendations through clear technical presentations and documentation.
  • Occasional domestic and international travel (<10%).

 What You Bring

• Ph.D. in Computer Science, Electrical Engineering, or a related field, with 5+ years of experience in system architecture for large-scale computing platforms, with a strong focus on AI workloads.
  • Proven hands-on experience developing analytical and event-driven simulation models for system-level performance evaluation.
  • Deep understanding of AI system hardware architectures, including compute, memory hierarchies, and high-performance interconnects.
  • Strong knowledge of modern and emerging AI workloads, including LLMs, DLRMs, and large-scale training and inference systems.
  • Demonstrated ability to translate workload characteristics and modeling results into actionable architectural design decisions.
  • Proficiency in Python, C++, and PyTorch for modeling, analysis, and experimentation.
  • Excellent written, verbal, and presentation communication skills, with the ability to influence technical direction across teams.
  • A collaborative mindset, intellectual curiosity, and resilience in tackling complex, open-ended system-level challenges.  
• You’re inclusive, adapting your style to the situation and diverse global norms of our people. 
• You approach challenges with curiosity and resilience, seeking data to help build.
• Understanding. You’re collaborative, building relationships, humbly offering support and openly welcoming approaches. 

#LI-SF1

Job Title: Principal Engineer, AI System Architect (Hardware)

 What You’ll Do
The Architecture Research Lab (ARL) focuses on addressing fundamental system-level bottlenecks in modern AI, particularly in memory capacity/bandwidth and system-scale communication. By leveraging Samsung’s world-class memory technologies, ARL explores and defines next-generation AI system architectures that deliver step-function improvements in performance, efficiency, and scalability.
We are seeking a Principal AI System Architect who will play a Technical Lead role in bridging AI workloads, system architecture, and hardware design. In this role, you will develop system-level performance models, drive architecture-level design decisions, and propose forward-looking AI system architectures that shape Samsung’s long-term AI platform strategy.

Location: Daily onsite presence at our San Jose office in alignment with our Flexible Work policy

Job ID: 42852

• • Technically Lead the architecture team with strong  direction, shaping system‑architecture strategy and advancing key innovations
  • Conduct system-level architectural research for next-generation AI systems, spanning compute, memory, and interconnect/network subsystems.
• Develop and maintain analytical and simulation-based system modeling frameworks to evaluate AI workloads and identify performance, scalability, and efficiency bottlenecks at rack- and system-scale. 
• Analyze representative and emerging AI workloads (e.g., LLMs, DLRMs, and future AI models) to derive architecture requirements and trade-offs across compute, memory, networking, and power.  
• Drive architecture-level design decisions through quantitative modeling, design-space exploration, and performance/power projections. 
• Perform comparative studies of alternative system architectures, reporting performance and performance-per-watt metrics to guide strategic technology choices. 
• Collaborate closely with cross-functional teams in hardware architecture, memory, interconnect, and system engineering to align modeling insights with implementation realities.  
• Communicate architectural insights and recommendations through clear technical presentations and documentation.   
• Occasional domestic and international travel (<10%).

 What You Bring

• Ph.D. in Computer Science, Electrical Engineering, or a related field preferred,  with 15+ years of experience in system architecture for large-scale computing platforms, with a strong focus on AI workloads 
• Proven hands-on experience developing analytical and event-driven simulation models for system-level performance evaluation. 
• Deep understanding of AI system hardware architectures, including compute, memory hierarchies, and high-performance interconnects.
• Strong knowledge of modern and emerging AI workloads, including LLMs, DLRMs, and large-scale training and inference systems.
• Demonstrated ability to translate workload characteristics and modeling results into actionable architectural design decisions.
• Proficiency in Python, C++, and PyTorch for modeling, analysis, and experimentation. 
• Excellent written, verbal, and presentation communication skills, with the ability to influence technical direction across teams.
• A collaborative mindset, intellectual curiosity, and resilience in tackling complex, open-ended system-level challenges. 
• You’re inclusive, adapting your style to the situation and diverse global norms of our people. 
• You approach challenges with curiosity and resilience, seeking data to help build understanding.
• You’re collaborative, building relationships, humbly offering support and openly welcoming approaches.
• Innovative and creative, you proactively explore new ideas and adapt quickly to change.

#LI-SF1

About the Role
We are seeking a Biomedical AI Engineer to design and deploy agentic AI systems that can reason over biomedical knowledge, plan multi-step analyses, and autonomously integrate diverse scientific data sources to accelerate therapeutic discovery.

This role goes beyond traditional LLM + RAG pipelines. You will build AI agents that can retrieve, synthesize, evaluate, and act on biomedical information across literature, omics datasets, and clinical records operating as intelligent systems embedded within discovery workflows.

Key Responsibilities

• Design and implement agentic AI architectures capable of multi-step reasoning, planning, and tool use in biomedical contexts.
• Develop LLM-based agents that dynamically retrieve, rank, and synthesize knowledge from scientific literature, knowledge graphs, omics datasets, and clinical data.
• Build memory and feedback mechanisms that allow agents to refine hypotheses, update context, and adapt to evolving data.
• Integrate external tools (analysis pipelines, simulation engines, statistical models, databases) into autonomous agent workflows.
• Architect scalable systems that combine structured and unstructured biomedical data within production-grade AI environments.
• Collaborate closely with computational biologists, translational scientists, and software engineers to embed agentic systems into real-world discovery pipelines.
• Evaluate robustness, reliability, and interpretability of autonomous systems in high-stakes biomedical settings.

Qualifications

• Degree in Computer Science, Machine Learning, Computational Biology, Biomedical Informatics, or related field.
• Strong hands-on experience with large language models, including fine-tuning, alignment, and structured prompting.
• Experience building agent-based systems or complex LLM orchestration frameworks (e.g., multi-agent systems, tool-using LLMs, planning modules).
• Proficiency in Python and modern ML frameworks (PyTorch, JAX, TensorFlow).
• Experience working with large-scale biomedical datasets (genomics, transcriptomics, clinical records, or scientific corpora).

Preferred

• Experience designing autonomous research assistants or AI systems that perform multi-step scientific reasoning.
• Familiarity with knowledge graphs, hybrid symbolic-neural systems, or multimodal foundation models.
• Understanding of privacy, security, and regulatory considerations in healthcare AI.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $190,000 - $280,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

• Develop multimodal foundation models spanning image and molecular data
• Design approaches that unify representation learning and generative modeling
• Train large-scale models on structured, high-dimensional datasets
• Explore cross-modal alignment, prediction, and generation
• Build scalable systems for data processing, training, and evaluation
• Work in a research-driven environment with evolving problem definitions

• Experience with representation learning (self-supervised, contrastive, masked modeling, etc.)
• Experience with generative modeling (diffusion, autoregressive models, VAEs, or related approaches)
• Proficiency in Python, ML frameworks, and CI/CD (PyTorch, JAX, etc.)

• Work on multimodal learning or cross-domain representation learning
• Experience with image data, molecular / omics-like data, or both
• Familiarity with large-scale training

• Exposure to biological or scientific datasets
• Experience with paired or partially aligned multimodal data
• Comfortable working in open-ended, evolving problem spaces

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $170,000 - $240,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

About the Role
We are looking for an AI Scientist to join our team at the intersection of machine learning and single-cell biology. This role will focus on developing and applying foundation models to large-scale perturb-seq and single-cell datasets to uncover new biological mechanisms and therapeutic opportunities. You will help design scalable ML architectures that can extract insight from high-dimensional perturbation data and integrate across multi-omic modalities.

Key Responsibilities

• Design, train, and refine foundation models tailored to perturb-seq and other single-cell datasets.
  Build pipelines for preprocessing, normalization, and integration of large-scale single-cell and perturbation data.
• Apply ML/AI approaches to model cellular responses to perturbations and identify causal biological insights.
• Collaborate with experimental biologists to align computational methods with experimental design and discovery goals.
• Develop multimodal integration approaches across transcriptomic, epigenomic, and proteomic single-cell readouts.
• Publish methods and results in top scientific journals and present at conferences.
  
  

Qualifications

• PhD or equivalent in Computational Biology, Computer Science, Bioinformatics, or related discipline.
• Strong expertise in single-cell data analysis, particularly perturb-seq 
• Hands-on experience with foundation models or large-scale self-supervised learning (e.g., transformers, variational autoencoders).
• Strong coding skills in Python, ML frameworks (PyTorch/TensorFlow), and single-cell analysis tools (Scanpy, Seurat).
• Experience in developing scalable ML methods for large biological datasets.
  
  

Preferred

• Background in causal inference, generative models, or representation learning for biological systems.
• Familiarity with multi-omics integration and cross-modal foundation models.
• Track record of impactful publications in computational biology, machine learning, or related fields.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $150,000 - $240,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

Expression of Interest

We know that for the most talented engineers, the right opportunity is about more than just a job title, it’s about the right challenge at the right time. Even if our current openings don't perfectly fit your timing and interests today, we still want to hear from you. We view this as a priority pathway to connect with curious, driven MLEs whose unique expertise can help us architect the next generation of planet-scale ML systems. 

At Moloco, our mission is to empower the global digital economy by turning massive first-party data into measurable business outcomes. Whether it’s optimizing real-time bidding for Moloco Ads or building AI-native stacks for Streaming and Commerce, we’re looking for engineers to help us lead the shift toward a more performance-driven, AI-powered internet.

If you’re excited to scale and innovate in a fast-moving environment, share your profile and we will reach out the moment we see a potential match for your experiences and future goals.

About the Role

As a Machine Learning Engineer at Moloco, you will design, train, and deploy the large‑scale models that power our programmatic advertising and commerce media products. You will work at the heart of our real-time bidding and pricing systems, helping shape an end-to-end ML ecosystem that processes billions of daily events. Your work will directly improve marketplace performance for global advertisers and publishers by optimizing for relevance, ROI, and user experience at a scale few companies can match.

The Opportunity

• Architect and iterate on high-performance models that improve ad relevance, click-through rates, and conversion performance.
• Productionize and maintain scalable ML pipelines - from data ingestion to online inference - on top of planet-scale infrastructure.
• Extract insights from massive datasets of user behavior and auction signals to define new features and refine modeling strategies.
• Translate business goals (revenue, ROI, engagement) into concrete modeling challenges and success metrics in collaboration with Product and Data Science.
• Validate innovation through rigorous experimentation, including A/B tests, offline evaluations, and counterfactual analyses.
• Balance marketplace health by implementing models that harmonize advertiser value with a high-quality user experience.
• Enhance system reliability by refining feature stores, monitoring data quality, and establishing robust debugging practices.
• Drive platform evolution, contributing to ML tools and guidelines that increase experimentation velocity and deployment speed.
• Optimize for performance, partnering with Infra teams to reduce latency and improve throughput for low-cost, high-scale decisioning.
• Elevate technical excellence by sharing best practices in modeling and production ML with the broader engineering team.

Expertise We Value:

MLEs at Moloco are hands-on builders of some of the world’s highest-scale ML workloads. They bridge technical innovation with global revenue outcomes, owning the critical systems that define our next generation of machine learning and optimization platforms.

While every journey is unique, we find that the most successful MLEs at Moloco bring a deep technical foundation in the following areas:

• Production ML at Scale: 5-12+ years of experience delivering ML solutions in high-stakes production environments (e.g., Ads, Recommenders, Search, or Marketplaces), with a track record of scaling models for massive throughput and low-latency requirements.
• Algorithmic Mastery: A strong foundation in ML and statistics applied to real-world business challenges, with expertise in areas such as ranking, calibration, exploration-exploitation, causal inference, or multi‑objective optimization.
• Full-Lifecycle Engineering: Deep understanding of the end-to-end ML lifecycle, including data pipelining, feature engineering, model architecture, inference optimization, and the deployment of models into online systems.
• Technical Versatility: Proficiency across a modern ML toolkit (Python, SQL, and frameworks like TensorFlow or PyTorch) and experience leveraging data processing stacks like Spark, Beam, or Flink to deliver results at scale.
• Operational Stewardship: Experience ensuring the long-term health of ML systems in live environments—monitoring performance, diagnosing drift, and iterating based on real-world feedback to maintain measurable impact.
• Technical Mentorship: A passion for advancing the team’s collective bar by sharing best practices for large-scale ML systems and guiding the technical direction of complex machine learning initiatives.

Our Tech Stack:

• Languages: Python, Go, C++
• ML Frameworks: TensorFlow, PyTorch, JAX
• Infrastructure: GCP, AWS, Kubernetes, Spark, BigQuery, BigTable

How You Work: 

• Your ethos is ownership
• You thrive in ambiguity and enjoy partnering with others to shape vague requirements into clear roadmaps with pragmatic tradeoffs.
• You take shared accountability for the end-to-end journey; communicating progress, surfacing risks early, and following through to ensure your work creates measurable value.
• You demonstrate strong judgment under uncertainty. 
• You prioritize based on long-term impact, over short-term noise, making deliberate decisions when information is incomplete.
• You explicitly weigh tradeoffs like speed vs. quality and remain agile enough to adjust your approach thoughtfully as new information/data emerges.
• You lead through clarity and active listening. 
• You reduce ambiguity for the team by asking the right questions upfront, tailor your communication to your audience, document your decisions, and bring helpful structure to complex discussions. 
• You provide thoughtful, evidence-based feedback when needed and align behind decisions once they are made.
• You collaborate early, instead of solving in isolation.
• You build trust across the organization by listening first and navigate conflicting needs with empathy, creating buy-in around priorities and scope. 
• You navigate technical tensions productively, disagreeing thoughtfully while maintaining momentum and strengthening professional relationships.
• You fall in love with the problem, not the solution
• You build for the long run, looking beyond immediate tasks to understand root causes, second-order effects, and the long-term health of our ML ecosystem. 
• When something breaks, you don’t just patch it; you seek structural improvements that prevent recurrence and elevate the technical bar for the entire organization.
• You prioritize customer impact and take action to make it real.
• You prioritize effective solutions that drive business impact over technical elegance, spotting opportunities that others might overlook. 
• You have the initiative to turn ideas into outcomes and the agency to identify and fix gaps, even when they aren’t yet on the formal roadmap.

You can apply for this role through our Open Positions page (or through our Internal Job Board if you are a current employee). We will review submissions on an ongoing basis.

The Impact You’ll Be Contributing to Moloco:

As a Senior Machine Learning Engineer on Moloco’s Ads Quality team, you’ll design and scale machine learning systems that directly improve ad relevance, ranking, and optimization. Your work will have a measurable impact on advertiser performance, revenue efficiency, and the overall user experience across Moloco’s ad platform.

The Opportunity:

• Design, build, and deploy large-scale ML systems for ad ranking, click-through prediction, and conversion optimization
• Develop and operate production pipelines that process hundreds of millions of ad requests per day with low-latency requirements
• Collaborate directly with customers and partners in Mandarin to understand business goals and deliver data-driven ML solutions
• Apply systematic, reproducible approaches to model training, evaluation, and continuous improvement
• Partner with the Machine Learning Infrastructure and Data teams to improve tooling, deployment pipelines, and training efficiency
• Lead design and code reviews to promote technical excellence and standardize ML practices across Ads teams
• Diagnose model performance, identify optimization opportunities, and execute experiments that drive measurable results
• Mentor engineers on best practices for ML experimentation, productionization, and scaling
• Work cross-functionally with product, infrastructure, and business teams to align technical innovations with product goals

How Do I Know if the Role is Right For Me?

• You have 7+ years of experience building and deploying ML systems at scale, ideally in AdTech, recommender systems, or search/ranking domains
• You’ve shipped models that directly improved key product or business metrics such as CTR, CVR, or ROI
• You’re fluent in Mandarin Chinese and skilled at collaborating with customers or partners in technical discussions
• You have strong software engineering fundamentals: data structures, algorithms, and system design and proficiency in Python (C++ or Java a plus)
• You’re experienced with modern ML frameworks such as PyTorch, TensorFlow, or JAX
• You’ve worked with distributed data and compute systems like Apache Beam, Dataflow, or Flume
• You understand how to build robust ML pipelines including data versioning, feature engineering, retraining, and model monitoring in production
• You have experience optimizing inference performance on GPUs, TPUs, or similar hardware accelerators
• You thrive in fast-moving, ambiguous environments and can translate complex technical work into measurable business outcomes
• You value collaboration, accountability, and building systems that scale across teams and markets

What You’ll Do:

As a strong AI and ML fundamentalist who is an expert at developing cutting-edge AI solutions to complex problems, you will develop code that eventually integrates into production and be responsible for:

• Design, implement, and evaluate novel machine learning and deep learning algorithms.
• Iterate on AI model development; starting from the data needed for training, architecture, input/output representations, evaluation, and deployment. 
• Collaborate with other researcher engineers to prototype and validate complex solutions from academic literature.
• Conduct experiments to benchmark new techniques and evaluate model behavior.
• Develop tools and frameworks to support scalable and reproducible research and development.
• Communicate research findings to leadership in a concise, and convincing manner.
• Stay current with the latest developments in AI/ML and identify relevant innovations.
• Assist in transitioning research prototypes into production-ready systems.

What You Need:

• M.S or PhD degree in Computer Science, or Computer Engineering with strong emphasis on AI and ML.
• Enjoys solving less-defined and complex problems
• Familiarity with good SW practices and development, including code quality, version control, etc.
• Very strong with ML frameworks such as Pytorch, or Tensorflow
• Good understanding of Transformer architectures, attention mechanisms, multi-modal foundation models, diffusion policies, fine-tuning, model distillation, mixture of experts, and other similar topics.
• Has strong ability to debug and determine requirements for AI models in terms of data, training, and evaluation.
• Is up to date with research literature and recent ML techniques and methodologies.

Bonus Qualifications:

• Experience with Reinforcement Learning, self-supervised training, and imitation learning is a plus.
• Experience developing VLA (Vision Language Action) models for robotic manipulation and mobility is a plus.
• Experience developing production AI models is a plus.
• Publications at top conferences are a plus.

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $160,000.00 - $180,000.00 Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.

Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.

What You’ll Do:

As a Staff AI and ML fundamentalist who is an expert at developing cutting-edge AI solutions to complex problems, you will develop code that eventually integrates into production and be responsible for:

• Design, implement, and evaluate novel machine learning and deep learning algorithms.
• Iterate on AI model development; starting from the data needed for training, architecture, input/output representations, evaluation, and deployment. 
• Collaborate with other researcher engineers to prototype and validate complex solutions from academic literature.
• Conduct experiments to benchmark new techniques and evaluate model behavior.
• Develop tools and frameworks to support scalable and reproducible research and development.
• Communicate research findings to leadership in a concise, and convincing manner.
• Stay current with the latest developments in AI/ML and identify relevant innovations.
• Assist in transitioning research prototypes into production-ready systems.

What You Need:

• M.S or PhD degree in Computer Science, or Computer Engineering with strong emphasis on AI and ML.
• Enjoys solving less-defined and complex problems
• Familiarity with good SW practices and development, including code quality, version control, etc.
• Very strong with ML frameworks such as Pytorch, or Tensorflow
• Good understanding of Transformer architectures, attention mechanisms, multi-modal foundation models, diffusion policies, fine-tuning, model distillation, mixture of experts, and other similar topics.
• Has strong ability to debug and determine requirements for AI models in terms of data, training, and evaluation.
• Is up to date with research literature and recent ML techniques and methodologies.

Bonus Qualifications:

• Experience with Reinforcement Learning, self-supervised training, and imitation learning is a plus.
• Experience developing VLA (Vision Language Action) models for robotic manipulation and mobility is a plus.
• Experience developing production AI models is a plus.
• Publications at top conferences are a plus.

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $190,000 - $240,000 Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.

Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.

What You’ll Do:

As a Principal AI and ML fundamentalist who is an expert at developing cutting-edge AI solutions to complex problems, you will develop code that eventually integrates into production and be responsible for:

• Design, implement, and evaluate novel machine learning and deep learning algorithms.
• Iterate on AI model development; starting from the data needed for training, architecture, input/output representations, evaluation, and deployment. 
• Collaborate with other researcher engineers to prototype and validate complex solutions from academic literature.
• Conduct experiments to benchmark new techniques and evaluate model behavior.
• Develop tools and frameworks to support scalable and reproducible research and development.
• Communicate research findings to leadership in a concise, and convincing manner.
• Stay current with the latest developments in AI/ML and identify relevant innovations.
• Assist in transitioning research prototypes into production-ready systems.

What You Need:

• M.S or PhD degree in Computer Science, or Computer Engineering with strong emphasis on AI and ML.
• Enjoys solving less-defined and complex problems
• Familiarity with good SW practices and development, including code quality, version control, etc.
• Very strong with ML frameworks such as Pytorch, or Tensorflow
• Good understanding of Transformer architectures, attention mechanisms, multi-modal foundation models, diffusion policies, fine-tuning, model distillation, mixture of experts, and other similar topics.
• Has strong ability to debug and determine requirements for AI models in terms of data, training, and evaluation.
• Is up to date with research literature and recent ML techniques and methodologies.

Bonus Qualifications:

• Experience with Reinforcement Learning, self-supervised training, and imitation learning is a plus.
• Experience developing VLA (Vision Language Action) models for robotic manipulation and mobility is a plus.
• Experience developing production AI models is a plus.
• Publications at top conferences are a plus.

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $270,000.00 - $340,000.00 Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.

Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.

What You’ll Do:

As a strong AI and ML fundamentalist who is an expert at developing cutting-edge AI solutions to complex problems, you will develop code that eventually integrates into production and be responsible for:

• Design, implement, and evaluate novel machine learning and deep learning algorithms.
• Iterate on AI model development; starting from the data needed for training, architecture, input/output representations, evaluation, and deployment. 
• Collaborate with other researcher engineers to prototype and validate complex solutions from academic literature.
• Conduct experiments to benchmark new techniques and evaluate model behavior.
• Develop tools and frameworks to support scalable and reproducible research and development.
• Communicate research findings to leadership in a concise, and convincing manner.
• Stay current with the latest developments in AI/ML and identify relevant innovations.
• Assist in transitioning research prototypes into production-ready systems.

What You Need:

• M.S or PhD degree in Computer Science, or Computer Engineering with strong emphasis on AI and ML.
• Enjoys solving less-defined and complex problems
• Familiarity with good SW practices and development, including code quality, version control, etc.
• Very strong with ML frameworks such as Pytorch, or Tensorflow
• Good understanding of Transformer architectures, attention mechanisms, multi-modal foundation models, diffusion policies, fine-tuning, model distillation, mixture of experts, and other similar topics.
• Has strong ability to debug and determine requirements for AI models in terms of data, training, and evaluation.
• Is up to date with research literature and recent ML techniques and methodologies.

Bonus Qualifications:

• Experience with Reinforcement Learning, self-supervised training, and imitation learning is a plus.
• Experience developing VLA (Vision Language Action) models for robotic manipulation and mobility is a plus.
• Experience developing production AI models is a plus.
• Publications at top conferences are a plus.

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $160,000.00 - $180,000.00 Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.

Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions.

The Mosaic AI organization enables companies to develop AI models and systems using their own data, with technologies ranging from pre-training LLMs from scratch to augmented generation using the latest retrieval techniques. Mosaic AI does so by producing novel science and putting it into production. Mosaic AI is committed to the belief that a company’s AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all.

Job Description

As a research engineer on the Scaling team, you will be responsible for keeping up with the latest developments in deep learning and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state-of-the-art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible.

The Impact you will have

As a research engineer on the Scaling Team at Databricks, you will: 

• Drive performance improvements through advanced optimization techniques including kernel fusion, mixed precision, memory layout optimization, tiling strategies, and tensorization for training-specific patterns
• Design, implement, and optimize high-performance GPU kernels for training workloads (e.g., attention mechanisms, custom layers, gradient computation, activation functions) targeting NVIDIA architectures
• Design and implement distributed training frameworks for large language models, including parallelism strategies (data, tensor, pipeline, ZeRO-based) and optimized communication patterns for gradient synchronization and collective operations
• Profile, debug, and optimize end-to-end training workflows to identify and resolve performance bottlenecks, applying memory optimization techniques like activation checkpointing, gradient sharding, and mixed precision training.

What We Look for

• BS/MS/PhD in Computer Science or related field with hands-on experience writing and tuning CUDA kernels for ML training applications, or hands-on experience in distributed training frameworks (PyTorch DDP, DeepSpeed, Megatron-LM, FSDP) 
• Strong understanding of NVIDIA GPU architecture (memory hierarchy, tensor cores, warp scheduling, SM occupancy) and proficiency with CUDA debugging/profiling tools (Nsight, NVProf)
• Deep understanding of parallelism techniques and memory optimization strategies for large-scale model training, with proven ability to debug and optimize distributed workloads
• Strong software engineering skills in Python and PyTorch, with experience supporting production training workflows and knowledge of LLM training dynamics including hyperparameter tuning and optimization strategies.

WHAT YOU’LL DO

• Guide DSP engineers in the execution of DSP trade studies and optimization of signal processing and machine learning algorithms for deployment on FPGAs and GPUs.
• Collaborate with a multidisciplinary team of software and hardware engineers to develop software defined radios; and direct DSP team in the engagement with the software & hardware team, including the implementation of DSP techniques into software and firmware and integration activities.
• Design and implement algorithms and techniques for RADAR systems
• Develop Modeling and Simulation (M&S) code for RADAR techniques and data analysis including Hardware-in-the Loop / Software-in-the-loop (HIL/SIL) testing
• Participate in laboratory and field testing of RF systems and techniques
• Participate in the maturation of RF systems into deployable systems and products

REQUIRED QUALIFICATIONS

• 7+ years with a BSEE or related field 
• Strong experience with DSP implementation for embedded devices and/or software defined radios.
• Strong knowledge of Python and MATLAB. Experience with CUDA or GPU accelerated frameworks like cuSignal is preferred.
• Experience with embedded devices, including FPGA, Nvidia Jetson, and Software Defined Radios.
• Skilled with Modeling and Simulation of RF systems including Radar and SAR
• Familiar with deep learning algorithms. Experience with ML frameworks such as TensorFlow and PyTorch is a plus.
• Familiar with wireless communication standards (Bluetooth, 3G/4G/5G, Wi-Fi, SINCGARS, MUOS, etc.).
• Excellent at balancing multiple projects at any given time and/or managing a larger team for a larger program.
• Enthusiastic about both working with a team and executing some work individually (depending on program scope).
• Experience with Electronic Warfare systems.
• Some travel required.
• Currently possesses and is able to maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• Masters or PhD degree in Electrical, Electronics, Computer Engineering, or related fields
• Defense, national security, or aerospace domain familiarity through industry or education.
• Extensive Digital Signal Processing (DSP) knowledge and experience
• Expertise in Synthetic Aperture Radar (SAR) and/or Inverse SAR (ISAR): Image formation, waveforms, phenomenology, modeling and simulation

ABOUT THE TEAM

Anduril Maritime delivers platforms, systems, and integrated effects in the maritime domain. Our autonomous vehicles (sub-surface and surface) are the cornerstone of these capabilities, and we continually strive to push the boundaries of the possible in terms of endurance, autonomy and mission capability. The Maritime team develops and maintains core products and payloads, and adapts and applies those products to serve a wide variety of defense, IC and commercial customers in US and international markets.

ABOUT THE JOB 

We are seeking a Senior Machine Learning/MLOps Engineer to join the Applied Intelligence team within Maritime Digital Production. You will lead the design, deployment, and sustainment of the AI-enabled backbone that connects data, tools, and people across our digital shipbuilding environment. This role focuses on operationalizing advanced models and architecting the industrial AI stack—selecting, integrating, and standardizing technologies that bring intelligence into production systems only where they deliver real value.

You’ll define and implement core components of the platform, including unified data and feature stores, vector databases, orchestration layers, and model-serving frameworks, while integrating off-the-shelf models for computer vision, OCR/IDP, speech, and retrieval-augmented generation. You’ll work across software, data, manufacturing, and corporate technology teams to translate real factory scenarios—inspection, root-cause analysis, receiving workflows, scheduling—into applied AI capabilities with clear human-in-the-loop controls, auditability, safety gates, and integrations with PLM, MES, CMMS, ERP, and the unified data plane.

This role demands technical range, judgment, and an instinct for when AI is the right tool versus when a simpler logic or workflow solution wins. You’ll collaborate across Anduril in a high-tech, fast-paced culture of innovation focused on delivering systems that work in the real world. If you want to shape how AI becomes a practical, reliable tool for production and logistics at scale, you’ll be helping build the future of digital shipbuilding and the next generation of maritime vehicles.

WHAT YOU’LL DO 

• Architect and own the AI/ML platform stack—from data ingestion, labeling, and feature engineering to model training, deployment, monitoring, and lifecycle management.
• Select, prioritize, and standardize industrial AI components including feature stores, vector databases + RAG, OCR/IDP and CV/STT providers, orchestration layers, and observability systems.
• Build model-serving and inference frameworks optimized for production environments, supporting real-time and batch execution across cloud, edge, and shop-floor systems.
• Translate factory scenarios (receiving, inspection, RCCA, scheduling) into applied AI workflows with defined human-in-the-loop gates, audit trails, and integration contracts with PLM, MES, CMMS, ERP, and the unified data plane.
• Implement event-driven data pipelines and telemetry systems that feed models with contextualized, real-time signals from production and logistics systems.
• Drive make/buy strategy by researching internal and vendor AI capabilities and recommending investments aligned to enterprise roadmaps, Anduril IP principles, and production constraints.
• Define and maintain model governance processes for validation, safety reviews, traceability, and rollback.
• Partner with Maritime platform teams and CorpTech to align architectures with enterprise data standards, ontologies, and compliance policies.
• Lead reliability engineering for deployed models—managing drift detection, retraining triggers, alerting, and operational SLOs.
• Mentor junior engineers and data scientists; establish best practices for MLOps, observability, data management, and secure handling of sensitive production data.

REQUIRED QUALIFICATIONS 

• Strong stakeholder management skills with proven experience aligning engineering, data, and manufacturing teams.
• 8+ years of experience in software or ML engineering with end-to-end delivery of production-grade AI/ML systems.
• Deep experience with MLOps: data acquisition, labeling, curation, pipeline management, model versioning, continuous integration, and model monitoring.
• Strong proficiency in Python and experience with deep learning frameworks (PyTorch, TensorFlow).
• Experience building and deploying containerized ML services using Docker and Kubernetes.
• Proficiency in data engineering, time-series data modeling, and working with semantic/ontology-driven data systems.
• Experience implementing observability for model performance, inference accuracy, and data drift.
• Familiarity with event-driven architectures, IoT/UNS patterns, and real-time systems integration.
• Excellent communication and documentation abilities; able to bridge research, platform, and production domains.
• Eligible to obtain and maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS 

• Experience applying AI/ML within manufacturing, logistics, industrial control, or production environments.
• Background with digital twins, predictive maintenance, OCR/IDP, CV, or STT model integrations.
• Experience with workflow/orchestration tools such as Flyte, Airflow, Kubeflow, or Temporal.
• Familiarity with GPU acceleration (CUDA) and inference optimization (TensorRT, Triton).
• Experience in regulated environments (NNPI/ITAR) and secure model/data governance.
• Demonstrated ability to mentor engineers and set technical direction for AI/ML infrastructure at scale.

WHAT YOU’LL DO

• Design, develop, and optimize digital signal processing (DSP) algorithms and systems for radio direction finding and direction-of-arrival (DoA) estimation in defense applications.  
• Collaborate with a multidisciplinary team of software and hardware engineers to develop software defined radios; and direct DSP team in the engagement with the software & hardware team, including the implementation of DSP techniques into software and firmware and integration activities.
• Implement high-performance, real-time signal processing chains on embedded and hardware platforms to support mission-critical sensing capabilities.  
• Develop Modeling and Simulation (M&S) code for RADAR techniques and data analysis including Hardware-in-the Loop / Software-in-the-loop (HIL/SIL) testing
• Participate in laboratory and field testing of RF systems and techniques
• Participate in the maturation of RF systems into deployable systems and products

REQUIRED QUALIFICATIONS

• 5+ years with a BSEE or related field
• Strong foundation in digital signal processing, comms theory, & system engineering with emphasis in direction finding algorithm implementation
• Hands-on experience with direction finding, angle-of-arrival estimation, and multi-antenna signal processing.  
• Strong experience with DSP implementation for embedded devices including FPGA, Nvidia Jetson, and Software Defined Radios and/or software defined radios.
• Strong knowledge of Python and MATLAB. Experience with CUDA or GPU accelerated frameworks like cuSignal is preferred.
• Skilled with Modeling and Simulation of RF systems including Radar and SAR
• Familiar with deep learning algorithms. 
• Familiar with wireless communication standards (Bluetooth, 3G/4G/5G, Wi-Fi, SINCGARS, MUOS, etc.).
• Enthusiastic about both working with a team and executing some work individually (depending on program scope).
• Experience with Electronic Warfare systems.
• Currently possesses and is able to maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• Masters or PhD degree in Electrical, Electronics, Computer Engineering, or related fields
• Experience with ML frameworks such as TensorFlow and PyTorch 
• Defense, national security, or aerospace domain familiarity through industry or education.
• Extensive Digital Signal Processing (DSP) knowledge and experience
• Expertise in Synthetic Aperture Radar (SAR) and/or Inverse SAR (ISAR): Image formation, waveforms, phenomenology, modeling and simulation

ABOUT THE TEAM

The Maneuver Dominance team at Anduril develops operationally relevant, multi-asset autonomy. We are focused on making large groups of autonomous systems work effectively together, with a particular emphasis on larger, more capable unmanned aerial vehicles. Our team specializes in integrating advanced perception and autonomy algorithms into complex aerial platforms, pushing the boundaries of what's possible in autonomous flight and mission execution. We develop cutting-edge Computer Vision and Autonomy algorithms to solve some of the hardest problems facing our customers, particularly in challenging and dynamic environments where robust perception is critical.

ABOUT THE JOB

We are seeking an experienced Computer Vision Engineer with a strong background in robotics to join our rapidly growing team in Costa Mesa, CA. In this role, you will be at the forefront of developing advanced perception systems for complex autonomous aerial platforms. Your expertise in computer vision algorithms, combined with your understanding of robotics principles, will be crucial in solving a wide variety of challenges involving visual perception, SLAM, motion planning, controls, and state estimation.

This role requires not only technical expertise in computer vision and robotics but also the ability to make pragmatic engineering tradeoffs, considering the unique constraints of aerial platforms. Your work will directly contribute to the seamless integration of Anduril's products, achieving critical outcomes in autonomous operations. This position demands strong systems-level knowledge and experience, as you'll be working on the intersection of computer vision, robotics, and autonomous systems. If you are passionate about pushing the boundaries of computer vision in robotics, possess a "Whatever It Takes" mindset, and can execute in an expedient, scalable, and pragmatic way while keeping the mission top-of-mind and making sound engineering decisions, then this role is for you.

WHAT YOU'LL DO

• Work at the intersection of 3D perception and computer vision, developing robust algorithms that power real-time decision-making for autonomous aerial systems.
• Develop and implement advanced structure from motion and SLAM algorithms to create accurate 3D models from multiple camera inputs in real-time.
• Integrate perception outputs with path planning algorithms to enable autonomous navigation in complex, unstructured environments
• Design experiments, data collection efforts, and curate training/evaluation sets to develop insights for both internal purposes and customers.
• Collaborate closely with robotics, software, and hardware teams to integrate perception algorithms into autonomous aerial systems.
• Work with vendors and government stakeholders to advance the state-of-the-art in perception and world modeling for autonomous aerial systems.

REQUIRED QUALIFICATIONS

• BS in Robotics, Computer Science, Mechatronics, Electrical Engineering, Mechanical Engineering, or related field.
• Strong knowledge of 3D computer vision concepts, including multi-view geometry, camera models, photogrammetry, and 3D reconstruction techniques.
• Fluency in standard domain libraries (numpy, opencv, pytorch, etc).
• Proven understanding of data structures, algorithms, concurrency, and code optimization.
• 4+ years of professional industry experience working with C++ or Rust programming languages.
• Experience deploying software to end customers, internal or external.
• Must be willing to travel 25%.
• Eligible to obtain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• MS or PhD in Robotics, Computer Science, Mechatronics, Electrical Engineering, Mechanical Engineering, or related field.
• Experience with perception systems for aerial robotics or other highly dynamic platforms.
• Experience with real-world sensor integrations, including LiDAR, RGB-D cameras, stereo cameras, or TOF cameras.
• Knowledge of path planning algorithms and their integration with perception systems in dynamic environments.
• Experience with GPU / CUDA programming for accelerated computer vision processing.

ABOUT THE TEAM

Anduril’s Tactical Recon & Strike (TRS) is a division with two missions: 1) build highly capable autonomous drones, and 2) build solid rocket motors at scale. We transform products like Ghost, Anvil, Bolt, and Altius from early concepts into fully operational capabilities by partnering closely with specialist engineering, operations, and production teams. Through our Anduril Rocket Motor Systems (RMS) team, we design and manufacture solid rocket motors using advanced materials, proprietary formulations, and high-volume production methods—delivering safe, reliable propulsion systems that support a wide range of mission requirements. TRS hires software engineers & hardware engineers, who are excited to build across a diverse and powerful portfolio—from autonomous aerial systems to high-performance solid rocket motors. Our teams contribute to highly capable autonomous robotics systems and propulsion products that operate reliably in the most demanding mission environment.

ABOUT THE JOB

We are seeking Senior Software Engineers specializing in Computer Vision and Machine Learning Engineering. You will leverage cutting-edge research to solve our most challenging perception problems for our UAVs, bringing deep expertise in Object Detection, Object Tracking, or related perception domains. This role requires hands-on proficiency in C++ and/or Python within a Linux environment. If you are passionate about tackling complex technical challenges in computer vision and perception, we encourage you to apply.

This position will be located at our headquarters in Costa Mesa, CA (relocation benefits provided).

WHAT YOU’LL DO

• Propose and prototype innovative solutions to solve real world problems, leveraging the latest state-of-the-art techniques in the field.
• Develop and maintain core libraries and runtime applications.
• Integrate classical and geometric methods in computer vision with ML methods.
• Work with ML and Data Infra team to construct various benchmarks for analyzing system performance.

REQUIRED QUALIFICATIONS

• MS or PhD in Machine Learning, Robotics or Computer Science, with emphasis on Computer Vision.
• BS in Computer Science, Machine Learning, Electrical Engineering, or related field.
• 4+ years experience developing and benchmarking ML algorithms on large-scale datasets.
• High proficiency in C++ development in a Linux environment.
• Experience deploying models with TensorRT and ONNX.
• Experience with Python development and deep learning frameworks such as PyTorch and TensorFlow.
• Experience writing and maintaining automated continuous integration tests.
• Experience in one or more of the following:
• Object Detection, Object Tracking, Instance Segmentation, Semantic Segmentation, Semantic change Detection.
• Experience in one or more of the following:
• Visual Odometry, SLAM, Multi-view Geometry, Structure from Motion, 3D Geometry, Discriminative Correlation Filters, Stereo, Neural 3D Reconstruction, RGB-D and LIDAR Sensor Fusion.
• Eligible to obtain and maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• Experience troubleshooting and analyzing remotely deployed software systems.
• Proficient in Python.
• Proficient in CUDA.

WHAT YOU’LL DO

• Design and implement algorithms and techniques for RADAR systems
• Develop Modeling and Simulation (M&S) code for RADAR techniques and data analysis including Hardware-in-the Loop / Software-in-the-loop (HIL/SIL) testing
• Guide DSP engineers in the execution of RADAR-DSP trade studies and optimization of signal processing and machine learning algorithms for deployment on FPGAs and GPUs.
• Participate in laboratory and field testing of RADAR-EW systems and techniques
• Participate in the maturation of RADAR-EW systems into deployable systems and products

REQUIRED QUALIFICATIONS

• Experience with Electronic Warfare systems.
• Experience with DSP algorithms and technique development for RADAR- Electronic Support Measures (ESM) and Electronic Counter Measure (ECM) systems.
• Strong experience with DSP implementation for embedded devices and/or software defined radios.
• Skilled with Modeling and Simulation of RF systems including Radar and SAR
• Strong knowledge of Python and MATLAB.
• Excellent at balancing multiple projects at any given time and/or managing a larger team for a larger program.
• Enthusiastic about both working with a team and executing some work individually (depending on program scope).
• Some travel required.
• Currently possesses and is able to maintain an active U.S. Secret/Top Secret security clearance.

PREFERRED QUALIFICATIONS

• Masters or PhD degree in Electrical, Electronics, Computer Engineering, or related fields.
• Experience with CUDA or GPU accelerated frameworks like cuSignal.
• Familiar with deep learning algorithms. Experience with ML frameworks such as TensorFlow and PyTorch is a plus.
• Experience with embedded devices, including FPGA, Nvidia Jetson, and Software Defined Radios.
• Expertise in Synthetic Aperture Radar (SAR) and/or Inverse SAR (ISAR): Image formation, waveforms, phenomenology, modeling and simulation.

WHAT YOU’LL DO

• Guide DSP engineers in the execution of DSP trade studies and optimization of signal processing and machine learning algorithms for deployment on FPGAs and GPUs.
• Collaborate with a multidisciplinary team of software and hardware engineers to develop software defined radios; and direct DSP team in the engagement with the software & hardware team, including the implementation of DSP techniques into software and firmware and integration activities.
• Design and implement algorithms and techniques for RADAR systems
• Develop Modeling and Simulation (M&S) code for RADAR techniques and data analysis including Hardware-in-the Loop / Software-in-the-loop (HIL/SIL) testing
• Participate in laboratory and field testing of RF systems and techniques
• Participate in the maturation of RF systems into deployable systems and products

REQUIRED QUALIFICATIONS

• 7+ years with a BSEE or related field 
• Strong experience with DSP implementation for embedded devices and/or software defined radios.
• Strong knowledge of Python and MATLAB. Experience with CUDA or GPU accelerated frameworks like cuSignal is preferred.
• Experience with embedded devices, including FPGA, Nvidia Jetson, and Software Defined Radios.
• Skilled with Modeling and Simulation of RF systems including Radar and SAR
• Familiar with deep learning algorithms. Experience with ML frameworks such as TensorFlow and PyTorch is a plus.
• Familiar with wireless communication standards (Bluetooth, 3G/4G/5G, Wi-Fi, SINCGARS, MUOS, etc.).
• Excellent at balancing multiple projects at any given time and/or managing a larger team for a larger program.
• Enthusiastic about both working with a team and executing some work individually (depending on program scope).
• Experience with Electronic Warfare systems.
• Some travel required.
• Currently possesses and is able to maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• Masters or PhD degree in Electrical, Electronics, Computer Engineering, or related fields
• Defense, national security, or aerospace domain familiarity through industry or education.
• Extensive Digital Signal Processing (DSP) knowledge and experience
• Expertise in Synthetic Aperture Radar (SAR) and/or Inverse SAR (ISAR): Image formation, waveforms, phenomenology, modeling and simulation

ABOUT THE TEAM

The Maneuver Dominance team at Anduril develops operationally relevant, multi-asset autonomy. We are focused on making large groups of autonomous systems work effectively together, with a particular emphasis on larger, more capable unmanned aerial vehicles. Our team specializes in integrating advanced perception and autonomy algorithms into complex aerial platforms, pushing the boundaries of what's possible in autonomous flight and mission execution. We develop cutting-edge Computer Vision and Autonomy algorithms to solve some of the hardest problems facing our customers, particularly in challenging and dynamic environments where robust perception is critical.

ABOUT THE JOB

We are seeking an experienced Computer Vision Engineer with a strong background in robotics to join our rapidly growing team in Costa Mesa, CA. In this role, you will be at the forefront of developing advanced perception systems for complex autonomous aerial platforms. Your expertise in computer vision algorithms, combined with your understanding of robotics principles, will be crucial in solving a wide variety of challenges involving visual perception, SLAM, motion planning, controls, and state estimation.

This role requires not only technical expertise in computer vision and robotics but also the ability to make pragmatic engineering tradeoffs, considering the unique constraints of aerial platforms. Your work will directly contribute to the seamless integration of Anduril's products, achieving critical outcomes in autonomous operations. This position demands strong systems-level knowledge and experience, as you'll be working on the intersection of computer vision, robotics, and autonomous systems. If you are passionate about pushing the boundaries of computer vision in robotics, possess a "Whatever It Takes" mindset, and can execute in an expedient, scalable, and pragmatic way while keeping the mission top-of-mind and making sound engineering decisions, then this role is for you.

WHAT YOU'LL DO

• Work at the intersection of 3D perception and computer vision, developing robust algorithms that power real-time decision-making for autonomous aerial systems.
• Develop and implement advanced structure from motion and SLAM algorithms to create accurate 3D models from multiple camera inputs in real-time.
• Integrate perception outputs with path planning algorithms to enable autonomous navigation in complex, unstructured environments
• Design experiments, data collection efforts, and curate training/evaluation sets to develop insights for both internal purposes and customers.
• Collaborate closely with robotics, software, and hardware teams to integrate perception algorithms into autonomous aerial systems.
• Work with vendors and government stakeholders to advance the state-of-the-art in perception and world modeling for autonomous aerial systems.

REQUIRED QUALIFICATIONS

• BS in Robotics, Computer Science, Mechatronics, Electrical Engineering, Mechanical Engineering, or related field.
• Strong knowledge of 3D computer vision concepts, including multi-view geometry, camera models, photogrammetry, and 3D reconstruction techniques.
• Fluency in standard domain libraries (numpy, opencv, pytorch, etc).
• Proven understanding of data structures, algorithms, concurrency, and code optimization.
• 6+ years of professional industry experience working with C++ or Rust programming languages.
• Experience deploying software to end customers, internal or external.
• Must be willing to travel 25%.
• Eligible to obtain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• MS or PhD in Robotics, Computer Science, Mechatronics, Electrical Engineering, Mechanical Engineering, or related field.
• Experience with perception systems for aerial robotics or other highly dynamic platforms.
• Experience with real-world sensor integrations, including LiDAR, RGB-D cameras, stereo cameras, or TOF cameras.
• Knowledge of path planning algorithms and their integration with perception systems in dynamic environments.
• Experience with GPU / CUDA programming for accelerated computer vision processing.

Why You'll Love This Role

You will work closely with the founding team and a group of highly-skilled engineers to shape the future of AI-enabled Security/Observability platforms. You will play a central role in bringing integrating cutting-edge AI/ML technologies to the Cribl Product suite to help solve real customer problems.  You will work closely with development partners and key stakeholders to iteratively design, develop, and deliver products and surfaces that will delight our customers.

On top of it all you will have fun. Cribl strives to be a great place to work for everyone.

As An Active Member Of Our Team, You Will...

• Design, train, and evaluate machine learning models across a range of research and applied AI initiatives
• Run rapid, iterative experiments to test hypotheses and surface insights that drive model improvements
• Collaborate closely with researchers and engineers to translate cutting-edge academic advances into practical, production-ready systems
• Build and maintain robust ML pipelines for data ingestion, feature engineering, model training, and evaluation
• Optimize model performance through fine-tuning, hyperparameter search, and architecture experimentation
• Contribute to a culture of rigorous experimentation; tracking results, documenting findings, and sharing learnings with the broader team
• Stay current with the latest developments in ML and AI research, and proactively identify opportunities to apply them
• This position may require stand-by, on-call, or off-hours duties during critical research or deployment milestones

If You've Got It - We Want It

• Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field with 5+ years of industry or research experience (Master's or PhD a plus)
• Deep hands-on experience training and evaluating ML models, including language models
• Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow
• Familiarity with MLOps tooling and infrastructure (e.g., MLflow, Weights & Biases, Kubeflow, or similar)
• Solid understanding of modern NLP, computer vision, and/or reinforcement learning techniques
• Strong ability to move fast without sacrificing rigor; you know when to prototype and when to productionize
• Excellent communication skills with the ability to clearly present experimental results to both technical and non-technical stakeholders

Salary Range ($230,000 - $275,000)

The salary for this role is dependent on geographic location. The salary offered within the range described will be based on the individual candidate’s job-related knowledge, skills, and experience.  In addition to a competitive salary, Cribl also offers a generous benefits package which includes health, dental, vision, short-term disability, and life insurance, paid holidays and paid time off, a fertility treatment benefit, 401(k), equity, and eligibility for a discretionary company-wide bonus.

#LI-JB1
#LI-Remote

What You Will Learn:

• Real-world ML benchmarking workflows from model to hardware.
• Performance tuning and optimization techniques.
• How ML applications are tested, validated, and productized.
• Collaboration across software, hardware, and research teams.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

As a C++ Machine Learning Engineer on the AI Models team at Tenstorrent, you’ll work on the training framework behind our most advanced models. You’ll write high-performance C++ code, shape how new layers and operators are implemented, and help models scale across our custom silicon. If you enjoy building the guts of ML systems and seeing them run fast, this role is for you.

This role is hybrid, based out of Santa Clara, CA.

We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who You Are

• Strong in C++ and low-level systems programming, especially in performance-critical code.
• Comfortable thinking in tensors, memory layout, and compiler graphs.
• Familiar with PyTorch and curious about how frameworks map to hardware.
• A builder who enjoys solving technical puzzles and digging into the details.

What We Need

• Extend and optimize our ML training framework with new ops, layers, and training features.
• Debug and tune model performance on Tenstorrent chips.
• Work with compiler and kernel teams to make sure models compile and run as expected.
• Support integration of real-world models and help bring them into production.

What You Will Learn

• How ML frameworks and compilers connect at the system level.
• How to translate training workloads into low-level operations optimized for custom silicon.
• How large-scale model training works under the hood, from memory layout to operator fusion.
• What it takes to build infrastructure that supports fast iteration in research and production.

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

We’re looking for a Field Application Engineer who’s wired for AI/ML, fluent in real-world problem-solving, and excited to build with the people actually using what we make. You will collaborate closely with the sales team and enterprise customers, leveraging your deep technical knowledge in AI to drive the adoption of our products and solutions. This is a customer-facing role that requires both technical expertise and excellent communication skills to convey complex technical concepts to non-technical stakeholders.

This role is hybrid, based out of Santa Clara, CA.  

We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who You Are

• You’ve lived in the AI/ML trenches, whether as a field engineer, a solutions architect, or the one tapped in when things needed to “just work.”
• You speak both machine and human. Whether it’s a researcher or a skeptical executive, you know how to break things down and bring them to life.
• You’re fired up about generative models, LLMs, and the edge of what’s possible when software meets purpose-built silicon.
• Work directly with customers in meetings, presentations, and workshops to understand their technical challenges and provide effective solutions.
• Partner closely with sales operations and product teams to provide feedback from customers and help shape future product enhancements.

What We Need

• Strong customer-facing skills with 5+ years of relevant technical, enterprise experience (such as Sales Engineer, Solutions Engineer, or Technical Account Manager).
• Your field insight will help shape our roadmap, our features, and the way we show up for developers.
• Proven expertise in AI technologies and frameworks, including machine learning, deep learning, natural language processing (NLP),computer vision, PyTorch or TensorFlow.
• Experience with embedded systems, FPGA Architecture or AI accelerators. Familiarity with hardware/software co-optimization is often critical for efficient inference at the edge.
• Good understanding of data center, server architecture and deployment, thermal/power, and infrastructure management.

What You Will Learn

• How to explore and push the boundaries of AI performance on custom silicon and help developers do the same.
• What it’s like to build the future from scratch, working alongside teams creating hardware, software, and everything in between.
• To master the craft of fine-tuning LLMs, optimizing vision models, and building AI pipelines that run at scale.
• An understanding of why field roles drive real impact turning on-the-ground insight into product breakthroughs and platform momentum.

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

Join the team revolutionizing AI computing at Tenstorrent. You'll work on TT-Forge, our MLIR-based compiler that enables developers to run AI on all configurations of Tenstorrent hardware using an open-source, performant, and general-purpose compiler. You will be at the forefront of the AI hardware revolution, building compiler technologies that redefine what’s possible.

 This role is hybrid, and can be based out of Santa Clara, CA; Austin, TX; or Toronto; ON.

We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who You Are

• A passionate software engineer eager to work on compiler technologies and the challenges of AI hardware, whether from compilers, systems, or broader software backgrounds.
• Fluent in C++ and Python, with experience building complex systems that bridge high-level frameworks to low-level execution.
• Excited by compiler optimization and machine learning, with experience in PyTorch, JAX, TensorFlow, or deep systems programming.
• A collaborative problem-solver who thrives in open-source and enjoys working closely with hardware and software engineers.

What We Need

• A drive to solve novel challenges in AI compilation, from optimizing computational graphs to creating custom dialects and transformation passes.
• Experience or strong interest in MLIR and how modular compiler frameworks connect AI models to advanced hardware.
• Motivation to build technology that impacts the future of AI, knowing your work will enable the next wave of breakthroughs.

What You Will Learn

• How to build open-source compiler frameworks supporting diverse AI models and workloads, including training and multi-chip scaling.
• Deep expertise in compiler technologies including custom MLIR dialects (TTIR, TTNN, TTKernel) and transformation passes.
• New methods for human-in-the-loop compiler optimization using TT-Explorer, making advanced tuning tools usable by all developers.
• How compiler technology powers Tenstorrent’s mission to deliver affordable, open-source AI computing in a highly competitive space.

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

Tenstorrent is seeking an Physical Design Engineer to lead  cross-functional efforts to solve complex physical design challenges and develop end-to-end RTL-to-GDS methodologies across advanced nodes, with a strong focus on PPA and runtime improvements. The engineer will architect, integrate, and deploy AI/ML-driven solutions into production physical design flows, creating custom CAD tools and partnering with internal teams and EDA vendors to drive next-generation, ML-enabled capabilities. 

This role is hybrid, based out of Santa Clara, CA or Austin, TX or Fort Collins, CO.

We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who you are

• BS in Electrical or Computer Engineering (or equivalent experience) with 5+ years in Physical Design CAD methodology at advanced nodes.
• Proven track record improving PPA and/or runtime on high-performance, low-power taped-out designs.
• Hands-on with industry-standard EDA tools (e.g., Fusion Compiler) across synthesis, P&R, STA, signoff, and hierarchical flows.
• Strong Python/Tcl and data skills, with interest or experience in ML frameworks (PyTorch, TensorFlow), and the ability to drive complex projects independently.

What we need

• Lead and contribute to cross-functional efforts solving complex physical design challenges across IPs, projects, and advanced technology nodes.
• Develop and enhance RTL-to-GDS methodologies, including floorplanning, synthesis, P&R, STA, signoff, and assembly.
• Architect and deploy AI/ML-driven solutions in production flows to improve engineering efficiency, turnaround time, and QoR.
• Optimize EDA tools and custom CAD flows using data-driven and ML-based techniques, in close collaboration with verification, extraction, timing, DFT, and EDA vendors.

What you will learn

• How to scale AI/ML-driven methodologies across diverse products and advanced technology nodes in real production flows.
• New ways to blend classical EDA algorithms with modern ML techniques to push PPA and runtime limits.
• Best practices for deploying, validating, and monitoring ML models in production CAD environments.
• How to influence next-generation ML-enabled EDA tools and collaborate deeply with cross-functional teams (PV, extraction, timing, DFT).

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

This position requires access to technology that requires a U.S. export license for persons whose most recent country of citizenship or permanent residence is a U.S. EAR Country Groups D:1, E1, or E2 country. 

The Company:

Faraday Future is a California-based technology company focused on the design, engineering, and development of intelligent, connected electric vehicles and related artificial intelligence–enabled technologies.

Founded in 2014, the Company’s mission is to disrupt the automotive and technology industries by creating user-centric, technology-first experiences. The Company, together with its controlled subsidiaries, operates across multiple technology-driven areas, including AI electric vehicles, robotics, and its crypto business (AIXC), all under its upgraded Global EAI Industry Bridge Strategy, marking the beginning of a new chapter in AI mobility and Web3 integration. The Company aims to leverage the latest technologies and world’s best talent to realize exciting new possibilities across all of these lines. Faraday Future’s automotive business exemplifies its vision for luxury, innovation, and performance, while its FX strategy aims to introduce mass production models equipped with state-of-the-art luxury technology derived from the FF brand, targeted towards a broader market with middle-to-low price range offerings. FF is committed to redefining mobility through AI innovation. Join us in shaping the future of intelligent transportation and technology by creating something new, something connected, and something with a true global impact.

Your Role:

We are building the next generation of intelligent robots. As a leader in Robotics AI Model, you will own the critical pipeline that transforms pretrained foundation models into deployable robot policies — turning general-purpose AI into systems that can reliably manipulate objects, navigate environments, and perform complex physical tasks in the real world.

This role sits at the intersection of embodied AI, robot learning, and foundation model adaptation. You will work across the full post-training lifecycle: curating demonstration data, fine-tuning vision-language-action (VLA) models or world models, training reinforcement learning policies in simulation, validating behaviors on real hardware, and optimizing models for on-robot inference. Your work will directly determine how capable, safe, and generalizable our robots are.

Key Responsibilities:

Model Post-Training & Fine-Tuning

• Design and execute post-training pipelines for VLA and visuomotor policy models (e.g., diffusion policies, ACT, flow matching), including supervised fine-tuning (SFT), reinforcement learning (RL), and preference-based optimization
• Fine-tune pretrained robot foundation models on task-specific demonstration datasets for dexterous manipulation, locomotion, whole-body control, and multi-step task sequencing
• Develop and iterate on reward functions, verifiers, and RL training loops (PPO, GRPO, RLVR) to improve policy success rate and robustness in simulation and real-world deployment
• Apply parameter-efficient fine-tuning methods (LoRA, QLoRA, OFT) to adapt large models to new tasks and robot embodiments under compute constraints

Data Pipeline & Curation

• Build and manage large-scale robot demonstration data pipelines: teleoperation data collection, action tokenization (e.g., FAST tokenizer), data augmentation, quality filtering, and dataset versioning
• Define data collection strategies across robot platforms, collaborating with robot operators and data labeling teams to ensure dataset diversity and coverage
• Integrate multi-modal sensory data (RGB, depth, proprioception, force/torque, tactile) into coherent training datasets

Simulation & Sim-to-Real Transfer

• Build and maintain simulation environments (Isaac Sim, MuJoCo, SAPIEN) for scalable policy training, including domain randomization, asset generation, and task definition
• Address sim-to-real transfer challenges through visual augmentation, action space calibration, dynamics randomization, and systematic real-world validation
• Design and run large-scale distributed RL training across GPU clusters for locomotion and manipulation policies

Evaluation & Deployment

• Build evaluation and benchmarking infrastructure: automated success-rate tracking, sim evaluation harnesses, real-robot A/B testing, and regression monitoring
• Optimize models for on-robot inference: quantization (INT8/FP8), action chunking, latency reduction, and real-time control loop integration
• Collaborate with controls, perception, and hardware teams to integrate learned policies into the full robot software stack

Research & Innovation

• Track and adopt state-of-the-art research in robot foundation models, generalist policies, and embodied AI post-training (e.g., π₀/π₀.5, OpenVLA OFT, RT-2, Octo, Helix)
• Contribute to internal research efforts on topics such as multi-embodiment transfer, long-horizon task learning, open-world generalization, and human-in-the-loop policy improvement

Basic Qualifications:

• Master’s or PhD in Robotics, Computer Science, Machine Learning, or a closely related field
• 3+ years of hands-on experience in robot learning, including imitation learning, behavior cloning, or visuomotor policy training on real or simulated robots
• Deep expertise in at least one post-training paradigm: SFT on robot demonstrations, RL-based policy optimization, or diffusion/flow-matching policy training
• Strong PyTorch skills with experience training and debugging models at scale; familiarity with distributed training (FSDP, DeepSpeed)
• Practical experience with robot simulation platforms (Isaac Sim, MuJoCo, PyBullet, or SAPIEN) and sim-to-real workflows
• Understanding of action representations for robotics: continuous control, discrete tokenization, action chunking, and diffusion-based action generation
• Solid Python engineering; comfortable working with ROS/ROS2, real-time control systems, and robot hardware integration
• Ability to independently drive projects from research prototype to real-robot deployment

Preferred Qualifications:

• Experience fine-tuning VLA models such as π₀, OpenVLA, RT-2, Octo, or similar generalist robot policies
• Hands-on experience with real robot platforms: humanoids, bi-manual arms (ALOHA), mobile manipulators, or dexterous hands
• Experience with large-scale teleoperation data collection systems and robot fleet management
• Familiarity with RLHF/DPO/GRPO applied to robotic policy alignment and human preference learning
• Experience building or contributing to robot learning infrastructure (LeRobot, robomimic, openpi, etc.)
• Publications at top robotics or ML venues (CoRL, RSS, ICRA, NeurIPS, ICML, ICLR)
• Knowledge of on-device model optimization: TensorRT, ONNX Runtime, model pruning, and edge deployment for embodied AI

Salary Range:

($150,000-$180,000 DOE), plus benefits and incentive plans

Perks + Benefits

• Healthcare + dental + vision benefits (Free for you/discounted for family)
• 401(k) options
• Casual dress code + relaxed work environment
• Culturally diverse, progressive atmosphere

Faraday Future is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

About the role

At Applied Intuition, you will:

• Develop, integrate, and adapt cutting-edge AI/ML algorithms running on the perception autonomy stack to collect relevant information across a suite of platform sensors
• Create interfacing software to autonomously control sensors (e.g., EO, IR, acoustics, radar, and RF)
• Collaborate across the sensor, tracking, and autonomy teams to ensure seamless deployment of heterogeneous platform swarms in on-site DoD testing and demonstration events
• Deploy containerized solutions to embedded Linux devices, leveraging computer-in-the-loop testing and profiling, and efficiently collecting performance data
• Interact with the DoD customer to understand their use cases, requirements, and triage needs during field events to deliver a superior customer experience
• Work closely with our existing team to internally triage technical problems and scope
• Carefully communicate and document ongoing work to ensure internal flexibility in a fast paced environment as well as clarify progress with external customers
• Drive execution of simulation tooling to playback sensors, platforms, and autonomy in post processing field test analysis
• Implement improvement plans for future integration efforts based on simulation analysis and customer feedback

We're looking for someone who has:

• MS or PhD in Electrical Engineering, Computer Engineering, Robotic Engineering, Computer Science, Optimization, or equivalent OR 5+ years of relevant experience working with sensor algorithms, hardware, and HIL software integration
• Experience with multiple sensor modalities (e.g., EO, IR, lidar, radar, sonar, acoustics, etc.)Core understanding of sensor physics and sensor control parameters
• Experience training and deploying ML algorithms (python, pytorch, tensorflow) onto integrated systems (onnx, C++ models)
• Familiarity with tracking basics (e.g., Kalman filters) and optimal sensor fusion
• Experience working comfortably in Linux and Docker
• Prior experience with remote software development, ability to handle and process large datasets, and learn new software and algorithms as needed with little supervision

Travel Requirements:

• Must be willing to travel as projects requires, usually for SW/HW integration and/or demonstrations; estimated average travel is every 1-2 months for 2-5 days (10-20%)
• Travel-adverse candidates are encouraged to inquire about relocation assistance to HQ in Poway, CA

Security Requirements:

• Must be a U.S. Citizen
• Must hold or be eligible to obtain and maintain a U.S. security clearance

For more information about U.S. security clearances: click here.

Nice to have:

• Proficiency with modern C++ development (2011, 2017, 2020, smart pointers, etc.), CMAKE, Python and Bash
• PhD in computer science or electrical engineering with AI/ML focus
• Experience with robotic swarm or multi-agent systems and optimization   
• Strong tracking and sensor fusion background
• Current U.S. SECRET security clearance

Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.

Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position.

Please reference the job posting’s subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is: $140,000 to $220,000 USD annually.

About the Role

We're seeking an exceptional Senior Engineering Leader to build and lead a high-performing engineering team focused on design and development of a distributed multi-tenant AI inference SaaS platform. Platform development responsibilities include but are not limited to software design, development and testing for multiple domains such as inference engines (AI/ML, program and compiler analysis), core platform services, and observability. This role sits at the intersection of systems engineering, AI/ML operations, and product development, requiring both deep technical expertise and proven leadership capabilities.

As a leader at Gruve, you'll drive the technical vision and execution of critical infrastructure that enables our AI capabilities at scale. You'll work closely with cross-functional partners including research scientists, product managers, and other engineering leaders to deliver robust, performant systems that power our AI products.

This position is based in the United States and reports to the SVP of Inferencing and Infrastructure Management

Key Responsibilities

• Team Leadership & Development: Build, mentor, and scale a world-class engineering team of 10-15+ engineers. Foster a culture of technical
• Excellence, collaboration, and continuous learning. Conduct performance reviews, career development planning, and succession planning.
• Technical Strategy & Architecture: Define and execute the technical roadmap for AI inference infrastructure, AI toolchains, and AI software development. Make critical architectural decisions that balance performance, scalability, maintainability, and cost.
• Compiler Design & Optimization: Lead the development of AI inference systems and optimizations for AI workloads, including graph optimization, kernel fusion, and hardware-specific code generation to maximize inference performance.
• AI Model Development & Deployment: Oversee the end-to-end lifecycle of AI models from development through production deployment, including model fine-tuning, quantization, distillation, and serving infrastructure.
• Inference API & Platform Development: Drive the design and implementation of scalable, low-latency inference APIs and platforms that serve models reliably at production scale with strict SLA requirements.
• Spec-Driven Development: Champion rigorous engineering practices including comprehensive technical specifications, design reviews, and documentation to ensure alignment and quality across complex projects.
• Cross-Functional Collaboration: Partner effectively with research, product, and business stakeholders to translate requirements into technical solutions and communicate progress, trade-offs, and risks clearly.
• Delivery & Execution: Own quarterly planning, roadmap prioritization, and on-time delivery of major initiatives. Establish metrics and KPIs to measure team performance and system health.

Basic Qualifications

• 10-15+ years of software engineering experience with at least 5+ years in engineering leadership roles managing teams of 5+ engineers
• Proven track record of building and scaling high-performing engineering teams in high-growth technology companies
• Deep expertise in systems programming languages (C++, Go, Rust, or similar) and architecture design
• Strong background in AI model design, optimization, or adjacent systems-level programming (LLVM, MLIR, XLA, or similar frameworks)
• Hands-on experience with AI/ML model development, training, and inference systems
• Experience with model fine-tuning techniques and deployment optimization (quantization, pruning, etc.)
• Demonstrated ability to design and build production-grade APIs and distributed systems
• Strong understanding of spec-driven development processes and engineering best practices · Excellent communication skills with ability to influence across all levels of the organization
• Demonstrated ability to work effectively with teams across multiple time zones
• Bachelor's degree in Computer Science, Engineering, or related technical field (or equivalent practical experience)

Preferred Qualifications

• Master's or PhD in Computer Science, Machine Learning, or related field
• Experience at leading AI/ML companies or research labs (OpenAI, Google DeepMind, Meta AI, Anthropic, etc.)
• Direct experience with modern ML frameworks (PyTorch, JAX, TensorFlow) and their compilation stacks
• Background in GPU programming (CUDA, Triton) and hardware acceleration for ML workloads
• Experience with transformer architectures and large language model (LLM) inference optimization
• Track record of shipping production ML systems serving millions of requests per day
• Contributions to open-source compiler or ML infrastructure projects
• Experience with cloud infrastructure (AWS, GCP, Azure) and containerization/orchestration (Kubernetes, Docker)
• Previous experience scaling teams from <10 to 20+ engineers

Salary Range 

$240,000 - $300,000 USD + Benefits

This position is with Gruve and is an on-site role based at the Gruve headquarters in Redwood City, California.

‍

Who we are

Neros is a defense technology company rebuilding America’s drone industrial base. We design and manufacture high-performance unmanned systems that are tested in combat, iterated at startup speed, and built at massive scale. Our team culture is fast, hands-on, and obsessed with closing the gap between design and deployment.

As drones transform the character of warfare, Neros is delivering the systems the West needs to compete on the modern battlefield and deter the adversaries of democracy. We’re hiring engineers, operators, and builders who want to move fast, take on extreme ownership, and get capability into the hands of warfighters in months, not years.

What you will be doing

The Autonomy Computer Vision Engineer will be responsible for developing and implementing cutting-edge computer vision algorithms to be deployed onboard Neros drones. This role involves designing, testing, and optimizing algorithms for real-time operation in autonomous systems, ensuring high performance and reliability in diverse environments. The candidate will collaborate closely with cross-functional teams, including robotics engineers, software developers, and hardware engineers, to integrate vision-based solutions into autonomous drone platforms.

You should have the following

• 3+ years of experience in computer vision, robotics, or related fields
• Proven experience in developing algorithms for real-time systems, preferably for autonomous platforms
• Strong proficiency in programming languages such as Python and C++
• Expertise in computer vision libraries and tools like OpenCV, TensorFlow, PyTorch, or similar
• Experience with SLAM, object detection, and image segmentation techniques
• Familiarity with UAVs and drone systems
• Knowledge of real-time system constraints
• Proficiency in debugging, testing, and validating algorithms in simulation and real-world environments

US Salary Range

$150,000 - $200,000 USD

The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are considered part of Neros' total compensation package.

We’re an equal opportunity employer. We welcome all applicants without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

What We're Looking For

We are seeking a highly skilled Research Engineer to work on optimizing training and inference workloads on compute accelerators and clusters, through the Lightning Thunder compiler and the broader PyTorch Lightning ecosystem. This role sits at the intersection of deep learning research, compiler development, and large-scale system optimization. You’ll be shaping technology that pushes the boundaries of model performance and efficiency, creating foundational software that will impact the entire machine learning ecosystem.

This role is based in one of our hubs (NYC, SF, Seattle, or London), with a minimum of 2 in-office days per week and occasional team and company offsites.

What You'll Do

• Develop performance-oriented model optimizations at multiple levels:
• Graph-level (e.g., operator fusion, kernel scheduling, memory planning)
• Kernel-level (CUDA, Triton, custom operators for specialized hardware)
• System-level (distributed training across GPUs/TPUs, inference serving at scale)
• Advance the Thunder compiler by building optimization passes, graph transformations, and integration hooks to accelerate training and inference workloads.
• Work across the software stack to ensure optimizations are accessible to end users through clean APIs, automated tooling, and seamless integration with PyTorch Lightning.
  Design and implement profiling and debugging tools to analyze model execution, identify bottlenecks, and guide optimization strategies.
• Collaborate with hardware vendors and ecosystem partners to ensure Thunder runs efficiently across diverse backends (NVIDIA, AMD, TPU, specialized accelerators).
• Contribute to open-source projects by developing new features, improving documentation, and supporting community adoption.
• Engage with researchers and engineers in the community, providing guidance on performance tuning and advocating for Thunder as the go-to optimization layer in ML workflows.
• Work cross-functionally with Lightning’s product and engineering teams to ensure compiler and optimization improvements align with the broader product vision.

What You’ll Need

• Strong expertise with deep learning frameworks such as PyTorch
• Hands-on experience with model optimization techniques, including graph-level optimizations, quantization, pruning, mixed precision, or memory-efficient training.
• Knowledge of distributed systems and parallelism strategies (data/model/pipeline parallelism, checkpointing, elastic scaling).
• Familiarity with software engineering practices: designing APIs, building robust tooling, testing, CI/CD for performance-sensitive systems.
• Excellent collaboration and communication skills, with the ability to partner across research, engineering, and external contributors.
• Bachelor’s degree in Computer Science, Engineering, or a related field.

Nice-to-Haves

• Experience with CUDA, Triton, or other GPU programming models for developing custom kernels.
• Deep understanding of deep learning compiler internals (IR design, operator fusion, scheduling, optimization passes) or proven work in performance-critical software.
• Proven track record contributing to open-source projects in ML, HPC, or compiler domains.
• Advanced degree (Master’s or PhD) in machine learning, compilers, or systems highly preferred.

Compensation

Shopmonkey's vision is to help every shop thrive by equipping them with the tools they need to run and grow their business. Our cloud based all-in-one shop management software takes owners and technicians from quote to cashing out a satisfied customer. Our software has a modern and intuitive UI and our backend is powered by the latest technologies so our clients can focus on the things they do best. As a Senior ML Engineer at Shopmonkey, you will be a part of a globally distributed engineering team working closely with your product and design counterparts. You will have the chance to work on the frontier of ML modeling, data pipelines, MLOps, and agentic AI systems to meet real-world auto shop needs. Shopmonkey has the structured data, workflows, and operational maturity to deliver ML powered systems that are not only intelligent but trusted and useful. You’ll move fast to bring ML systems from discovery all the way through production, helping to shape the future of the automotive care experience. For any Bay area based candidates, this would be hybrid with 2-3 days/week office at our Morgan Hill, CA office for collaboration. 

What you will do:

• Design, build, and ship production-ready ML models across a range of problem spaces: regression, classification, clustering, ranking, and recommendation systems.
• Conduct end-to-end development of ML systems: data gathering, experimentation, feature engineering, model training, evaluation, deployment, and monitoring.
• Define and track model performance metrics, run A/B tests, and iterate based on real-world feedback.
• Help design and implement shared feature stores so that reusable features can serve multiple models consistently in both batch and real-time contexts.
• Work within a modern MLOps environment to ensure scalable and reliable deployment of models.
• Contribute to training infrastructure, model versioning, and CI/CD pipelines for ML workflows.
• Work closely with data scientists and data engineers to develop data driven solutions that are high impact for businesses.
• Translate complex ML workflows into digestible updates for cross-functional stakeholders.
• Contribute to backlog velocity by owning appropriate tickets and delivering high-impact work in a collaborative, fast-paced environment.
• Implement NLP and LLM-powered components for sentiment analysis, real-time conversation evaluation, and behavior optimization.
• Contribute to analytics and predictive features such as no-show prediction and sentiment dashboards.
• Help build and ship AI agents that help automate key auto-shop business processes.

We are looking for people who have:

• Minimum of 5+ years of industry experience in applied machine learning; advanced degrees (Master’s or PhD) may offset years of experience.
• Proven experience shipping models into production (not just proof-of-concepts or notebooks).
• Proficiency in Python; experience with ML frameworks like PyTorch or Tensorflow.
• Strong foundations in classical ML/DL. Including some of the following: regression, classification, clustering, ranking, feature engineering, model evaluation, and experimentation.
• Bachelor’s degree in a STEM field, or equivalent practical experience.
• Strong collaboration and communication skills—comfortable working with PMs, designers, engineers and other cross functional team members.

Nice to have:

Candidates should have some experience in one or more of the following areas.

• Understanding of MLOps principles: model versioning, orchestration, evaluation, monitoring, model serving, and CI/CD for ML. 
• Understanding of MLOps, and experience with modern tooling like MLFlow, DVC, Airflow, etc.
• Experience with LLMs and NLP frameworks (e.g., TensorFlow, Hugging Face, LangChain).
• Experience with/interest in LLM workflows and agentic workflows
• Cloud infrastructure experience, (e.g. GCP, AWS).
• Familiarity with vector databases (e.g. Pinecone, pgvector) and embedding-based retrieval or similarity search.
• Strong SQL skills for working with large-scale data.
• Experience designing or contributing to feature stores (e.g. Feast, VertexAI Feature Store, Tecton) for shared, reusable feature pipelines.

Bonus Points:

• Prior experience working at a high growth startup.
• Experience building consumer-facing agents in vertical SaaS, in the automotive industry (business or consumers).
• Background in data processing or real-time analytics.
• Experience with Snowflake or other large-scale data warehouse solutions.

In the United States, the range is typically a salary of $165,000 to $200,000 + bonus + equity + benefits. The range provided is Shopmonkey’s reasonable estimate of the base compensation for this role. The actual amount will be based on job-related and non-discriminatory factors such as location, experience, training, skills, and abilities. Consult with your Recruiter during the initial call to determine a more targeted range based on these job-related factors. In addition to this base compensation company stock options and benefits as outlined below are included.