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

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

What we offer:

• Competitive compensation package including equity and annual bonuses
• Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Cigna, and  MetLife (including a medical plan with infertility benefits)
• MetLife Legal Services, Identity & Fraud Protection, Hospital Indemnity Insurance, Accident Insurance, & Critical Illness Insurance
• Flexible PTO, 10 paid holidays, and generous parental leave policies
• Our office is centrally located in Mountain View, CA
• Office perks: dog-friendly, free catered lunch, a fully stocked kitchen, and free EV charging
• Long Term Disability, Short Term Disability, Life Insurance
• Wellbeing Benefits - Headspace through Cigna, Calm through Kaiser, One Medical, Gympass, Spring Health through Cigna, Rula (mental health navigation) 
• Fidelity 401(k)
• Commuter, FSA, Dependent Care FSA, HSA
• Various incentive programs (referral bonuses, patent bonuses, etc.)

Cresta is on a mission to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. Our platform combines the best of AI and human intelligence to help contact centers discover customer insights and behavioral best practices, automate conversations and inefficient processes, and empower every team member to work smarter and faster. Born from the prestigious Stanford AI lab, Cresta's co-founder and chairman is Sebastian Thrun, the genius behind Google X, Waymo, Udacity, and more. Our leadership also includes CEO, Ping Wu, the co-founder of Google Contact Center AI and Vertex AI platform, and co-founder, Tim Shi, an early member of Open AI.

Join us on this thrilling journey to revolutionize the workforce with AI. The future of work is here, and it's at Cresta.

About the role:

We are looking for a motivated Data Science Intern to join our team. This role offers hands-on experience working with real-world data, building models, and supporting data-driven decision-making. You will collaborate with data scientists, engineers, and business stakeholders to solve meaningful problems.

What You'll Do :

• Collect, clean, and preprocess structured and unstructured data
• Perform exploratory data analysis to identify trends and insights
• Build and evaluate machine learning models under guidance
• Develop data visualizations and dashboards to communicate findings
• Assist in deploying models and monitoring their performance
• Work with large datasets using tools like Python, SQL, and cloud platforms
• Document processes, experiments, and results clearly
• Participate in team demos, feedback sessions, and learning opportunities.
• This role provides mentorship and exposure to customer-facing technical problem solving in a fast-moving AI/Product environment.

What We're Looking For:

• Enrolled in a Bachelor’s or Master’s degree program in Computer Science, Engineering, or a related field.
• Experience writing code in Python (or another general-purpose language).
• Strong interest in artificial intelligence, machine learning, or software engineering.
• Basic understanding of statistics and machine learning concepts
• Familiarity with libraries such as Pandas, NumPy, Scikit-learn, or TensorFlow/PyTorch
• Experience with SQL and working with databases
• Strong analytical and problem-solving skills
• Excellent communication skills and willingness to collaborate with teammates and customers.

Nice-to-Haves

• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn)
• Familiarity with cloud platforms (AWS, GCP, or Azure)
• Knowledge of version control (Git)
• Exposure to big data tools (Spark, Hadoop) is a plus

This posting will be used to fill a newly-created role.

We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored.  If you are uncertain whether you have been contacted by an official Cresta employee, reach out to recruiting@cresta.com.

ENGINEERING - GAMES

What We Do

Unreal projects have been leading the pack of real-time entertainment with our constantly growing team of engineering experts. We’re always improving on the tools and technology that empower content developers worldwide.

What You'll Do

You will work with our team of engineers at the intersection of vision, language and machine learning to create state-of-the-art models for agentic vision tools. You will be responsible for the design, implementation and deployment of production-ready computer vision models that support game developers in our ecosystem (including scene generation and trained bots/agents), as well as agents for automated content verification (e.g. gameplay behavior).

In this role, you will

• Create and deliver production-ready, scalable and high-quality deep-learning models and associated algorithms for computer vision problems
• Critically assess the effectiveness of such models and make recommendations for the ongoing roadmap
• Methodically understand and assess the effectiveness of new data channels and support collection/creation of new ones

What we're looking for

• PhD in Computer Science, Mathematics or related field, 5+ years of relevant industry experience
• Proven track record creating innovative solutions for problems in Computer Vision and deploying them as production-level systems in industrial environments
• Expert, hands-on knowledge of:
  • Deep learning techniques for supervised, semi-supervised and unsupervised learning
  • Reinforcement learning, imitation learning, and related frameworks
  • Python and associated ML tools/frameworks (numpy, scipy, sklearn, pytorch) 
• Experience with working collaboratively with other developers, following a flexible/agile/lean approach
• Desirable:
  • Experience with architecting, scaling, securing and operating ML systems in the cloud (ideally AWS) at medium to large scale
  • Experience with 3D Vision/Graphics

EPIC JOB + EPIC BENEFITS = EPIC LIFE

Our intent is to cover all things that are medically necessary and improve the quality of life. We pay 100% of the premiums for both you and your dependents. Our coverage includes Medical, Dental, a Vision HRA, Long Term Disability, Life Insurance & a 401k with competitive match. We also offer a robust mental well-being program through Modern Health, which provides free therapy and coaching for employees & dependents. Throughout the year we celebrate our employees with events and company-wide paid breaks. We offer unlimited PTO and sick time and recognize individuals for 7 years of employment with a paid sabbatical.

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. 

Position Overview

Woolpert is hiring a Senior Software Engineer to join our dynamic Atlas Labs team supporting our Geospatial sector. This position reports to the Director of Product and AI. Atlas Labs oversees technology development for Woolpert’s Geospatial sector, including various types of AI model development, R&D, software infrastructure, and user-facing products.

We are unable to provide visa sponsorship for this position.  Applicants must already possess work authorization in the country the job is located.

What You Will Do:

• Contribute to the planning, research, design, architecture, development, and testing of Atlas Labs software features. You’ll write code daily, definitely in Python and possibly in C++ or JavaScript.
• Work as part of a cross-functional Scrum team with domain experts in AI/ML, Geospatial Data, Software Engineering, and GIS.
• Collaborate with internal and external users to ensure the correctness, quality, and availability of Atlas Labs software products.

What You Will Bring:

• Meaningful employment experience working on commercial software products
• Experience writing production code in Python, preferably dealing with large datasets
• Demonstrated experience or academic output in a relevant domain:
• Geospatial Data Processing
• Computer Vision
• AI & Machine Learning
• LiDAR
• Robotics/Self-Driving/Autonomy
• General familiarity with relevant technologies:
• Linux, Docker, and GitHub
• AI/ML frameworks (Tensorflow, Pytorch)
• Cloud platforms (Azure, AWS, Google)

Nice to Have:

• Familiarity with GIS applications like ESRI, QGIS, Google Earth
• Familiarity with orchestration frameworks like Kubernetes, AirFlow, MLFlow
• Programming experience in C++ or JavaScript
• Experience with Agile processes like Scrum

Benefits You Will Love

Certified as a Great Place to Work, Woolpert is one of the fastest-growing architecture, engineering, and geospatial companies in the world. With over 75 offices and countless projects around the globe, you’ll work on meaningful assignments that improve quality of life around the world. In addition to offering competitive pay, we provide employees with a robust set of unique benefits, including:

• Freedom to Work program: Set your own schedule and location (as appropriate).
• Principal program: Earn the opportunity to become an owner of the firm.
• Flexible paid time off/vacation: Take time off when it makes sense for you and your team.
• Career development: Explore a wide range of learning and growth opportunities within and across industries.
• Health, life, vision, and dental insurance: Cover all your medical bases.
• Paid sick time, retirement plan, fitness reimbursement, pet insurance, identity protection, technology stipend, employee assistance program, and more!

#LI-Hybrid

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: 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

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

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.

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.

• 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.

Mission Summary:

Motional’s onboard autonomous driving system team works at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional’s next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for Motional’s current and next-generation onboard autonomous driving system. If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you. We are hiring in a range of levels, from graduate engineers to Staff engineers.

What You'll Be Doing:

• Design and develop infrastructure software on various hardware platforms for applications such as vision processing, radar systems, safety monitoring, etc., to be run on self-driving vehicles.
• Design test harnesses for embedded software components and full systems
• Provide technical mentorship to engineers.
• Proactively work with cross-functional engineering teams to solve complex and interesting problems.
  
  

What We're Looking For:

• Experience with creating detailed requirements from use cases.
• Ability to lead a technical initiative, including breaking down work and guiding other engineers through execution.
• Experience writing software for embedded platforms in C and C++.
• Experience with Test-Driven Development (TDD).
• Experience working on embedded Linux / RTOSs.
• Experience working with networks (Ethernet, CAN etc.) and the common networking protocols.
• Experience with debugging on embedded platforms.
• Experience writing software in Python and experience doing automation with shell scripting.
• Experience working with ARM Cortex MCUs or Microprocessors.
  
  

Bonus Points (not required):

• Experience working with large data pipelines, and platforms that require deterministic execution.
• Experience using inter-system communication protocols such as I2C and SPI
• Experience deploying Machine Learning models.
• Experience working with GPUs.
• Experience working directly with the Linux kernel or Device Drivers.
• Experience with Simulation and Code Generation, and knowing when their use is appropriate.
• Experience working with Bazel.
• Experience integrating various sensors, including Cameras, IMUs, Radars, LIDARs.
• Experience with PyTorch, TensorFlow, ONNX, and/or other ML frameworks. 
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

Mission Summary:

Motional’s onboard autonomous driving system team works at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional’s next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for Motional’s current and next-generation onboard autonomous driving system. If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you. We are hiring in a range of levels, from graduate engineers to Staff engineers.

What You'll Be Doing:

• Design and develop infrastructure software on various hardware platforms for applications such as vision processing, radar systems, safety monitoring, etc., to be run on self-driving vehicles.
• Design test harnesses for embedded software components and full systems
• Provide technical mentorship to engineers.
• Proactively work with cross-functional engineering teams to solve complex and interesting problems.
  
  

What We're Looking For:

• Experience with creating detailed requirements from use cases.
• Ability to lead a technical initiative, including breaking down work and guiding other engineers through execution.
• Experience writing software for embedded platforms in C and C++.
• Experience with Test-Driven Development (TDD).
• Experience working on embedded Linux / RTOSs.
• Experience working with networks (Ethernet, CAN etc.) and the common networking protocols.
• Experience with debugging on embedded platforms.
• Experience writing software in Python and experience doing automation with shell scripting.
• Experience working with ARM Cortex MCUs or Microprocessors.
  
  

Bonus Points (not required):

• Experience working with large data pipelines, and platforms that require deterministic execution.
• Experience using inter-system communication protocols such as I2C and SPI
• Experience deploying Machine Learning models.
• Experience working with GPUs.
• Experience working directly with the Linux kernel or Device Drivers.
• Experience with Simulation and Code Generation, and knowing when their use is appropriate.
• Experience working with Bazel.
• Experience integrating various sensors, including Cameras, IMUs, Radars, LIDARs.
• Experience with PyTorch, TensorFlow, ONNX, and/or other ML frameworks. 
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

Mission Summary:

Motional’s onboard autonomous driving system team works at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional’s next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for Motional’s current and next-generation onboard autonomous driving system. If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you. We are hiring in a range of levels, from graduate engineers to Staff engineers.

What You'll Be Doing:

• Design and develop infrastructure software on various hardware platforms for applications such as vision processing, radar systems, safety monitoring, etc., to be run on self-driving vehicles.
• Design test harnesses for embedded software components and full systems
• Provide technical mentorship to engineers.
• Proactively work with cross-functional engineering teams to solve complex and interesting problems.
  
  

What We're Looking For:

• Experience with creating detailed requirements from use cases.
• Ability to lead a technical initiative, including breaking down work and guiding other engineers through execution.
• Experience writing software for embedded platforms in C and C++.
• Experience with Test-Driven Development (TDD).
• Experience working on embedded Linux / RTOSs.
• Experience working with networks (Ethernet, CAN etc.) and the common networking protocols.
• Experience with debugging on embedded platforms.
• Experience writing software in Python and experience doing automation with shell scripting.
• Experience working with ARM Cortex MCUs or Microprocessors.
  
  

Bonus Points (not required):

• Experience working with large data pipelines, and platforms that require deterministic execution.
• Experience using inter-system communication protocols such as I2C and SPI
• Experience deploying Machine Learning models.
• Experience working with GPUs.
• Experience working directly with the Linux kernel or Device Drivers.
• Experience with Simulation and Code Generation, and knowing when their use is appropriate.
• Experience working with Bazel.
• Experience integrating various sensors, including Cameras, IMUs, Radars, LIDARs.
• Experience with PyTorch, TensorFlow, ONNX, and/or other ML frameworks. 
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

About the Role
Our Platform Infrastructure team is the backbone of everything we do at Attentive, providing a resilient and cost-effective platform that seamlessly handles billions of events from over 100 million customers daily. We own everything from compute, persistence, and networking to observability and deployments. Joining our team offers a high-growth career opportunity to collaborate with some of the world’s most talented engineers in a high-performance, high-impact culture.

What You’ll Accomplish

• Spearhead FinOps initiatives to increase cost transparency and optimize resource utilization across teams
• Provide guidance and mentorship to engineers on cost-optimization best practices
• Collaborate with teams across the organization to implement cost-saving measures
• Analyze, troubleshoot, coordinate, and resolve complex infrastructure issues
• Proactively lead infrastructure initiatives that have a company-wide impact
• Partner with engineering teams to influence cost-effective architectural and design choices
• Develop automation workflows to enhance team productivity and efficiency
• Foster a culture of continuous improvement by encouraging innovative thinking and challenging established norms

Your Expertise

• Bachelor's degree in Computer Science, Engineering, or related field; Master’s degree preferred
• 2+ years of experience in FinOps or cloud cost management
• 5+ years of experience in cloud infrastructure management, development or related roles
• Proficiency in some of the following technologies: AWS, Datadog, Kubernetes, Vantage, Terraform, Java
• Strong analytical and problem-solving skills with a keen attention to detail
• Excellent communication and leadership abilities
• Ability to work collaboratively in a cross-functional team environment

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $180,000 - $240,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-MN1

By applying for this position, your data will be processed as per Attentive's Privacy Policy.

About the Role
We’re looking for a highly driven Senior Software Engineer to join our Streaming team, which powers the backbone of Attentive’s messaging and personalization platform. Our event streaming systems handle over 2 million messages per second and sit at the heart of how product and data engineering teams build real-time, customer-facing experiences.

What You’ll Accomplish

• Architect and evolve Attentive’s next-generation event streaming platform: Design high-throughput, low-latency solutions that power mission-critical messaging, personalization, and data integration use cases across Attentive’s ecosystem
• Enhance self-service for product engineering and data teams: Build and refine self-serve tools for event observability, debugging, load testing, and system configuration, empowering teams to experiment and ship quickly
• Simplify and modernize streaming architecture: Remove unnecessary abstraction layers, enable direct access for power users, and ensure the platform is flexible for both “paved path” and advanced use cases
• Solve complex distributed systems challenges: Improve event delivery reliability, cost efficiency, and system integration for real-time and batch workloads
• Champion best practices and technology selection: Stay ahead of industry advancements in event streaming, advocating for tools and approaches that balance innovation with long-term reliability
• Collaborate across engineering: Partner with product, data, and infrastructure teams to launch new customer-facing features, integrations, and scalable solutions built on streaming infrastructure

Your Expertise

• 5+ years experience architecting and supporting high-throughput, distributed systems at scale—especially those involving event streaming or messaging platforms
• Deep understanding of the internals of distributed streaming frameworks such as Kafka, Flink, Pulsar, and/or Spark
• Proficient in Java (Spring Boot) and familiar with modern development practices, including object-oriented design, data structures, and algorithms
• Able to debug issues across the stack—from message serialization and event schemas to network and JVM tuning—and communicate tradeoffs clearly
• Familiar with resource scheduling, data locality, and how infrastructure choices impact cost and system behavior
• Experience with observability and developer tooling for streaming (e.g., tracing, metrics, replay).Infrastructure-as-code expertise (Terraform, Helm), comfortable with Kubernetes (EKS) and cloud-native environments
• Track record of modernizing platforms: sunsetting legacy systems, moving to managed services, or implementing self-service capabilities
• Excited by new technologies, but pragmatic about introducing them—focused on solving real business problems

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $150,000-$210,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-AB2

By applying for this position, your data will be processed as per Attentive's Privacy Policy.

About the Role

Our Engineering team creates innovative product experiences that power personalized marketing at massive scale. We develop cutting-edge applications and systems that process 100s of billions of messages and events per year, enabling marketers to connect effectively with hundreds of millions of consumers. Joining our team offers a high-growth career opportunity to work with some of the world’s most talented engineers in a high-performance and high-impact culture.

As a Senior Software Engineer in our Intelligent Messaging, you will pioneer the future of personalized 1:1 marketing by architecting robust, scalable backend systems powered by advanced AI and LLMs, including cutting-edge Generative AI and GPT technologies. Collaborating with top-tier engineers, data scientists, product managers, and designers, you’ll craft the foundation and reshape the platform of multi-channel messaging experimentation to support innovative, AI-driven applications that empower marketers to forge deep, meaningful connections with consumers at scale. Your impactful work will drive the delivery of billions of tailored messages, transforming consumer shopping experiences and fueling success for the world’s leading brands.

What You’ll Accomplish

• Develop and maintain scalable backend systems for our customer-facing products, ensuring high performance and reliability.
• Collaborate with cross-functional teams to build applications that support multi-channel communications for marketers.
• Implement and optimize systems that process and deliver billions of messages daily.
• Improve code quality through code reviews, testing, and advocating for best practices.
• Identify and address technical debt to ensure the long-term health of our codebase.
• Drive architectural design and technical decisions, and stay current with emerging technologies to enhance our products.

Your Expertise

• 5+ years of professional experience in software development focusing on backend systems.
• Proficiency in Java, Python, or Go, with a strong understanding of object-oriented programming.
• Experience building and maintaining scalable, high-performance applications.
• Proven ability to collaborate effectively with cross-functional teams.
• Solid understanding of software development best practices, including code reviews, writing tests, and continuous integration.

Nice to Haves

• Experience with service-oriented architecture and distributed systems.
• Familiarity with AWS services and cloud infrastructure.
• Knowledge of databases such as DynamoDB, Postgres, or Redis.
• Experience with messaging systems or streaming platforms (e.g., Kafka, Pulsar).
• Familiarity with frontend development with React and TypeScript.
• Experience with DevOps practices and tools such as Docker and Kubernetes.

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS.
• Infrastructure tooling includes Istio, Datadog,Terraform, CloudFlare, and Helm.
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Kinesis, AirFlow, Postgres, Planetscale, and Redis, hosted via AWS.
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and PlaywrightOur automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas.

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $190,000 - $230,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-EZ1

By applying for this position, your data will be processed as per Attentive's Privacy Policy.

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads targeting, relevance modeling, auction optimization, measurement, and user experience. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Data Scientist to join our growing Ads Data Science team. As a Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve our understanding of the dynamics that drive the success of our advertising platform, and identify opportunities to accelerate that success. You will work closely with stakeholders across product, engineering, sales, marketing, and data to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Develop ML models & DS methods to for improved anomaly detection, prediction, pattern recognition
• Communicate findings and recommendations to stakeholders across the organization
• Collaborate with product, engineering, sales, and marketing partners to define product and program requirements and translate them into data science solutions
• Stay up-to-date on the latest advancements in machine learning and data science

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 3+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 2+ years of industry experience in applied science or data science roles
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

[Location: remote-friendly or any office location - SF, LA, CHI, NY]

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads targeting, relevance modeling, auction optimization, measurement, and user experience. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Data Scientist to join our growing Ads Data Science team. As a Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve our understanding of the dynamics that drive the success of our advertising platform, and identify opportunities to accelerate that success. You will work closely with stakeholders across product, engineering, sales, marketing, and data to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Develop ML models & DS methods to for improved anomaly detection, prediction, pattern recognition
• Communicate findings and recommendations to stakeholders across the organization
• Collaborate with product, engineering, sales, and marketing partners to define product and program requirements and translate them into data science solutions
• Stay up-to-date on the latest advancements in machine learning and data science

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 3+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 2+ years of industry experience in applied science or data science roles
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Senior Data Scientist to join our growing Ads Data Science team. As a Senior Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve the adoption and performance of our advertising platform through data-driven insights. You will work closely with product managers, engineers, and other data scientists to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform
• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Collaborate with product managers and engineers to define product requirements and translate them into data science solutions
• Develop ML models & DS methods to improve anomaly detection, prediction, & pattern recognition 
• Communicate findings and recommendations to stakeholders across the organization
• Stay up-to-date on the latest advancements in machine learning and data science
• Mentor and guide junior data scientists on the team

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 5+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 4+ years of industry experience in applied science or data science roles
• Platform experience and a deep understanding of the ads ecosystem
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

Location: US remote-friendly

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Senior Data Scientist to join our growing Ads Data Science team. As a Senior Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve the adoption and performance of our advertising platform through data-driven insights. You will work closely with product managers, engineers, and other data scientists to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform
• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Collaborate with product managers and engineers to define product requirements and translate them into data science solutions
• Develop ML models & DS methods to improve anomaly detection, prediction, & pattern recognition 
• Communicate findings and recommendations to stakeholders across the organization
• Stay up-to-date on the latest advancements in machine learning and data science
• Mentor and guide junior data scientists on the team

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 5+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 4+ years of industry experience in applied science or data science roles
• Platform experience and a deep understanding of the ads ecosystem
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave  

#LI-Remote

About the Role
The Onsite Customer Growth team builds the features that help Attentive’s customers grow directly on their websites. Our mission is to accelerate list growth and improve conversion by delivering creative, high performing onsite experiences powered by strong engineering and intelligent AI driven optimization.

What You’ll Accomplish

• Lead, mentor, and grow a high performing engineering team responsible for building the backend systems powering onsite customer growth products
• Set the technical vision and roadmap for backend services, APIs, and data driven systems that power personalized onsite experiences at scale
• Partner closely with AI, data, and product teams to develop intelligent capabilities that improve performance and user experience
• Ensure the reliability, scalability, and performance of the systems that support customer growth and real time user interactions
• Drive best practices in design discussions, code reviews, architecture decision making, and operational excellence
• Foster a learning oriented team culture that encourages collaboration, curiosity, ownership, and continuous improvement
• Own delivery of key product initiatives, balancing long term platform investments with near term business objectives
• Promote clean, maintainable, well tested code and high engineering standards across the team

Your Expertise

• 7+ years of professional backend software engineering experience, including at least two years managing or leading engineers
• Strong proficiency in one or more modern programming languages such as Java, or Typescript
• Experience designing and operating distributed systems, APIs, and microservice architectures at scale
• Hands on familiarity with cloud platforms such as AWS and containerization technologies such as Docker or Kubernetes
• Deep understanding of databases, messaging systems, or streaming technologies such as PostgreSQL, Redis, or Kafka
• Track record of building reliable, scalable, high throughput systems that support customer facing products
• Demonstrated ability to coach and develop engineers, drive team alignment, and create an inclusive, collaborative engineering environment
• Strong communication and cross functional partnership skills, with the ability to work effectively with AI, data, product, and design teams
• A mindset rooted in ownership, curiosity, and a passion for building meaningful systems that drive measurable customer impact

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $193,000 - $250,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-MN1

By applying for this position, your data will be processed as per Attentive's Privacy Policy.

As a Senior Software Engineer, you will be tasked with leading the architectural design and technical strategy for high-performance systems that process massive volumes of telemetry data while reducing costs and improving insights for enterprise customers. You will drive technical excellence and lead complex engineering initiatives at scale for the Observo.ai team, our cutting-edge AI-driven data pipeline optimization platform.

What Will You Do?

Primary responsibilities include:

• Lead the architectural design and technical roadmap for scalable, high-performance data processing pipelines capable of handling petabyte-scale telemetry data (logs, metrics, traces).
• Drive the development and optimization of ML-driven data routing and transformation engines to reduce customer data volumes by 80%+ while architecting real-time analytics systems using advanced machine learning and LLMs.
• Design cloud-native microservices and APIs that integrate seamlessly with major observability platforms (Splunk, Elastic, Datadog) while establishing robust monitoring, alerting, and observability solutions.
• Lead cross-functional technical initiatives and decision-making forums, collaborating with Product, Data Science, and DevOps teams to translate strategic vision into technical solutions and company-wide standards.
• Provide technical leadership and mentorship to senior and junior engineers, driving system performance and reliability optimization while establishing engineering best practices and culture.

What Skills and Knowledge Will You Bring?

Ideal candidates will have:

• 5+ years of software engineering experience focused on distributed systems, data engineering, or ML infrastructure with expert-level proficiency in Go, Rust, or Java.
• Extensive experience with cloud platforms (AWS, GCP, Azure), container orchestration (Kubernetes), and a proven track record leading and scaling data pipelines using Kafka, Spark, or Flink.
• Deep expertise in database technologies (SQL and NoSQL) and advanced experience with machine learning frameworks (TensorFlow, PyTorch) and MLOps practices for production ML systems.
• Expert knowledge of observability tools and standards, including Prometheus, Grafana, ELK stack, OpenTelemetry, and Parquet, alongside extensive experience with Infrastructure as Code (Terraform).
• Strong leadership and technical communication skills, with a track record of mentoring engineers, planning technical strategy, and driving decisions across multiple teams and stakeholders.

Why SentinelOne?

AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.

We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:

• Medical, Vision, Dental, 401(k), Commuter, Health and Dependent FSA
• Unlimited PTO
• Industry-leading gender-neutral parental leave
• Paid company holidays
• Paid sick time
• Employee stock purchase program
• Disability and life insurance
• Employee assistance program
• Gym membership reimbursement
• Cell phone reimbursement
• Numerous company-sponsored events, including regular happy hours and team-building events

THE ROLE

Despite the "Engineer" title, this isn't a typical back-end coding job. This is a pre-sales and architectural advisory role for someone who is part scientist, part consultant, and part communicator. At the Staff / Principal level, you are expected to be a hybrid heavy hitter — someone who can talk shop with PhD data scientists and then walk into a boardroom and explain the ROI to a CEO.

We aren't looking for your average expert. We're building a team of T-shaped professionals with:

• Deep Technical Roots — You know PyTorch, Kubernetes, and GPU clusters (NVIDIA/AMD) inside and out, and you know when XGBoost is a better choice than the latest frontier model.
• Broad Business Acumen — You understand verticals, e.g. how a hospital's AI needs differ from a hedge fund's, and can navigate both conversations with credibility.
• Collaborative Autonomy — With a global remit and potential for 30-60% travel, you are in charge of driving results within diverse collaborations.

We're building a small, global Applied AI team to work directly with enterprise customers and partners — helping them turn AI ambitions into production outcomes on Pure's platform. This team brings genuine research and production depth to customer-facing engagements: leading technical advisory sessions, shaping AI strategy for some of the world's largest companies, and contributing to Pure's growing reputation in AI through publications, conferences, and thought leadership.

The team also ensures Pure's account teams can effectively qualify and position AI advisory opportunities across their territories, and provides enablement to our internal field and channel partner communities. The role requires working cross-functionally across Solutions, Marketing, Alliances, Engineering, Enablement, and Sales to align initiatives and go-to-market campaigns — all while maintaining genuine technical depth in enterprise AI.

If this sounds like you, come join one of the most exciting teams at Pure.

WHAT YOU'LL DO:

• Lead technical discovery and advisory engagements with customers to identify high-value AI use cases relevant to their industry and data
• Advise on end-to-end AI deployment — model selection, training/fine-tuning strategies, inference optimization, data pipeline design, and evaluation/alignment/safety frameworks — optimized for Pure's platform
• Collaborate cross-functionally to qualify and position AI opportunities, and develop proof-of-value prototypes that translate technical performance into business outcomes
• Create AI enablement content for field teams, partners, and customers — technical walkthroughs, qualification guides, workshops, and vertical-specific use case frameworks
• Present at industry conferences, publish technical content and peer-reviewed research, and represent Pure in engagements with strategic technology partners (NVIDIA, AMD, cloud providers, MSPs)
• Operate autonomously in ambiguous environments — independently scoping high-impact initiatives and driving them to completion at the right pace

WHAT YOU BRING:

• Advanced degree in a quantitative field (Computer Science, Physics, Mathematics, Engineering, or related), or equivalent demonstrated through publications and production system experience
• 8+ years building and deploying AI/ML systems in cloud or on-prem environments
• Deep expertise in modern AI/ML — large language models, distributed training, inference optimization, agentic systems, evaluation/alignment frameworks, and classical ML
• Fluency with the modern AI stack (PyTorch, vLLM, Ray, Kubernetes) and data platforms (Spark, Snowflake, Kafka, etc.)
• Able to scope and carry out research projects that support critical business objectives, both independently and collaboratively
• Excellent written, verbal, and presentation skills — equally clear with hands-on data scientists and C-suite decision-makers

WHAT SETS YOU APART:

• Experience with large-scale AI infrastructure: GPU clusters, high-performance storage, containerized deployments
• Experience in customer-facing technical advisory or consulting roles with enterprise accounts
• Experience leading independent, multi-year research from concept to publication or large-scale production deployment
• Exposure to multiple industry verticals (financial services, healthcare, telco, manufacturing)
• Publication record, conference presentations, or recognized technical presence
• Background combining applied research with shipping production systems
• Familiarity with CRM/opportunity management systems (Salesforce preferred)

#LI-REMOTE

#LI-JL4

As a Senior Machine Learning Engineer, you will work on challenging problems leveraging state-of-art AI/ML to empower a new generation of Roblox experiences for our growing community of users. We are looking for senior AI/ML engineers to lead the vision of low compute cost, in experience machine learning at Roblox, taking leads on designing core components of on-device ML operations. We are designing a system for advancing model architecture, enabling more efficient deployment to cloud and client, while delivering on complex operations including Generative AI model deployment. The engineer will be driving the architecture optimization across a large range of compute devices, making efficient use of available compute resources. Join us in our exciting journey!

You will:

• Develop and implement state-of-the-art ML models
• Stay up-to-date with the latest research in ML and related fields, and apply this knowledge to improve the model performance
• Establish a pipeline for delivering Roblox ML model on range of computing devices
• Build cross-functional partnership on deployment and architecture optimization
• Design and implement primary components of the in-experience machine learning system.

You have:

• • 2+ years experience in developing machine learning models, preferably in image, video, audio or 3D representations with Python
  • A strong understanding of deep learning frameworks including PyTorch and Tensorflow.
  • Experience in shipping ML features in production environments, including low powered devices.
  • Excellent cross-functional skills, partnering with organization leaders, driving to a conclusion.
  • Knowledge in state-of-the-art deep learning network architectures and primitives.
  • Experience with model optimization techniques.

At Roblox, computer vision and graphics power the way our global community discovers, creates, and interacts on our virtual platform. This role involves building cutting-edge models to interpret and analyze every form of content—experiences, text, images, videos, and 3D avatars. Your work will directly influence core systems that drive the next generation of creation, search, recommendations, and trust & safety initiatives across our massive ecosystem.

We’re looking for PhD candidates passionate about the intersection of computer vision, graphics, and generative modeling. You’ll work on applied research and engineering projects with direct production impact — enabling new ways for creators and players to bring ideas to life.

Teams Hiring for This Role

• Content Understanding: Develop large-scale computer vision and multimodal models that classify, organize, and recommend 3D and visual content to improve user discovery, personalization, and safety.
• Account Identity: Focuses on various aspects of user identity from bot detection, alternate account detection graph, to age estimation based on behavioral and facial features.
• Safety AI Systems: Develop AI that automatically inspects and filters the vast array of user-generated content on Roblox – from images and videos to audio files, 3D meshes, and entire games. This includes CV models to detect unsafe images, audio analysis to screen sound and music, and novel techniques for 3D content and code moderation.

You Will:

• Design and implement foundation models for visual and 3D-based creation, search, and recommendations, ensuring a high level of fidelity, relevance, and ranking.
• Break down complex product requirements into iterative deliverable stages, moving applied research into high-scale production systems.
• Implement innovative visual and multi-modal models that power core Roblox functions (e.g., world creation, avatar systems, search, and recommendations).
• Build high precision facial age estimation across demographics from ground up including various fraud detection techniques for a robust and safe user identity system. 

You Have

• Possessing or pursuing a PhD in computer science, engineering, or a related field, with a thesis aligned to Roblox’s research areas.
• Expertise in one or more areas: computer vision, multimodal learning, 3D Graphics, or large-scale representation learning.
• Experience developing and training deep learning models using modern frameworks (PyTorch, TensorFlow, JAX).
• A strong research track record, evidenced by multiple publications and presentations in top-tier, peer-reviewed venues.
• Proficiency in one or more programming languages (e.g., Python, C++, Go, Java) and experience building and optimizing large-scale systems.

Apply now to be considered for anticipated positions.

You may redact age, date of birth, and dates of attendance/graduation from your resume if you prefer.

As you apply, you can find more information about our process by signing up for Speak_. You'll gain access to our practice assessment, comprehensive guides, FAQs, and modules designed to help you ace the hiring process.

At Roblox, we're on a mission to empower creators to build and share immersive experiences. As a member of the Roblox Studio team, you’ll be working on the most popular tool for game development in the world. Our Studio team is seeking an exceptional Machine Learning Engineer to push the boundaries of AI-assisted game development.

You'll improve the capabilities of Roblox Assistant and Code Assist, crafting the future of how games are built on our platform. Your work will directly impact millions of creators and players worldwide.

You Will:

• Advance Roblox Assistant's Reasoning: Pioneer innovative ways to improve our AI's ability to handle complex prompts. This may involve architecting novel models or fine-tuning innovative language models on diverse, large-scale datasets.
• Specialize LLMs for Roblox: Lead efforts to fine-tune large language models on Roblox's unique data model, tailoring innovative AI to our specific ecosystem. Your work will bridge the gap between general-purpose LLMs and the niche needs of interactive content development.
• Elevate Scripting Quality: Innovate on our Lua code data pipeline, developing sophisticated quality signals to ensure premier script generation.

You Have:

• Deep expertise in PyTorch or equivalent ML frameworks.
• Proficiency with distributed data processing systems like PySpark.
• Proven track record of deploying ML systems to production at scale.
• Strong understanding of transformer architectures and their applications.
• 3+ years of experience building ML systems / applications.
• A passion for game development, with extra points for Roblox Lua scripting experience.

As a Principal Machine Learning Engineer within the Creator Services Machine Intelligence team, you will focus on the research and development of Embodied AI and Behavioral Agents that revolutionize how games are created and played on Roblox. You will bridge the gap between cutting-edge research and massive-scale product application, building agents capable of complex 3D gameplay and unblocking many use cases across Roblox, from automated playtesting to ensure quality, to "Smart NPCs" with human-like movement and strategic reasoning, playing with real players in games.

You will work on Imitation Learning (IL), Reinforcement Learning (RL), Computer Vision, Computer Graphics, Robotics, and Agentic Reasoning to create generalizable agents that can perceive 3D environments, understand game rules, plan long-term strategies, and execute complex physics-based actions.

You Will:

• Report to the Engineering Manager of Creator Services Machine Intelligence.
• Design and implement foundation models for embodied agents that master both fluid, human-like movement and high-level strategic reasoning.
• Define the long-term roadmap for Game AI and Embodied Intelligence, acting as a technical bar-raiser for code quality and architectural design.
• Balance the exploration of cutting-edge deep learning research with the practical constraints of serving models to millions of concurrent users.
• Mentor fellow engineers and researchers, fostering a culture of technical excellence and scientific inquiry.
• Collaborate with Product Managers, Backend and Game Engine Engineers and other Roblox team members.

You Have:

• PhD or Master’s in Computer Science, Applied Math, or other field. A record of top-tier publications (e.g., NeurIPS, ICML, CVPR, AAAI, SIGGRAPH, etc) in embodied agents or related domains is a plus.
• 7+ years of experience as a Machine Learning Engineer or Research Scientist, applying research to tangible products.
• Deep technical understanding of Imitation Learning, Robotics, Reinforcement Learning, Computer Graphics and Vision, with experience working on low-latency motor control (human-like movement) and high-level strategic reasoning (game rules/goals).
• Proficiency in Python (PyTorch/TensorFlow) and familiarity with C#, C++, or similar systems languages.
• Experience training models on large-scale distributed clusters and understanding the challenges of inference in real-time gaming environments.
• A passion for bridging the gap between research and production, moving beyond academic benchmarks to launch scalable solutions that directly impact millions of users.

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

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.

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.

The Team

The Machine Learning Platform team builds the foundational technology that scales machine learning innovation across Upstart. As a Principal Machine Learning Engineer, you will work at the intersection of applied ML and platform engineering—collaborating closely with Research Scientists, Data Scientists, and ML Platform Engineers to design tools and systems that accelerate model development to ultimately improve predictive accuracy. Success in this role requires deep knowledge of ML throughout the entire modeling lifecycle - from data preparation to training and deployment to production.

In this role, you will lead engineering initiatives that turn high-impact modeling needs into scalable, reusable infrastructure. This includes building a unified embeddings platform for training, serving, and managing representations at scale; streamlining feature engineering pipelines to reduce manual steps and deliver new signals quickly; developing automated continuous-learning systems that handle data refresh, retraining, evaluation, and drift monitoring with minimal manual effort; and scaling our training pipelines to support larger datasets, more complex architectures, and faster experimentation.

Across all of these efforts, you will work backward from applied ML projects that meaningfully improve accuracy—using those real-world scenarios to harden the platform capabilities that enable ML teams across Upstart to innovate with greater speed, reliability, and impact.

How You’ll Make an Impact

• Scale ML innovation by building tools, infrastructure, and workflows that dramatically improve the speed and reliability of model development.
• Work backward from modeling needs to design systems that directly unlock gains in accuracy, efficiency, and scientific productivity.
• Explore new algorithms and methodologies for our machine learning models and develop tooling to support them
• Improve the entire ML lifecycle—from data readiness and feature development through training, evaluation, serving, and monitoring.
• Automate and standardize operational workflows, enabling scientists to focus on high-leverage modeling and analysis rather than manual pipelines.
• Define the roadmap for our next generation ML Platform, balancing near-term impact with long-term architectural scalability.
• Collaborate cross-functionally with Data Engineering, ML Platform, Pricing, and other teams to build reliable, end-to-end ML systems.

Your work will multiply the effectiveness of every ML team at Upstart—accelerating innovation and advancing our mission to make credit more accurate, accessible, and fair.

This is a high influence role suited for those who enjoy combining science innovation, with cross functional collaboration and advisory. 

Minimum Qualifications

• 7+ years of hands-on experience in applied machine learning, with strong exposure to production-scale modeling efforts.
• Demonstrated expertise in end-to-end model development: data prep, feature engineering, training, evaluation, and deployment.
• Experience working in high-scale, ML-driven product environments—especially in fintech, pricing, or risk modeling.
• Proficiency in Python and core ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn, XGBoost).
• Ability to work autonomously and lead technical direction in ambiguous, high-impact domains.
• Experience collaborating with cross-functional teams including ML scientists, engineers, and product partners.
• Ability to bridge engineering and science teams, and influence technical strategy across disciplines.
• Numerically-savvy and smart with ability to operate at a fast pace
• Master’s degree or PhD in a quantitative discipline, or equivalent additional professional experience. 

Preferred Qualifications

• Practical experience optimizing ML workflows using CUDA/GPU acceleration.
• Background in feature store design, embedding architecture, or synthetic data generation for model training.
• Proven track record of improving model accuracy in production environments with measurable business outcomes.
• Familiarity with modern experimentation frameworks, hyperparameter tuning tools, and automated model selection techniques.

Benefits:

• Comprehensive Healthcare Benefits
• 401k Matching
• Workspace benefits for your home office
• Personal & Professional development funds
• Family Planning Support
• Flexible Vacation (please use them!) & Reddit Global Wellness Days
• 4+ months paid Parental Leave
• Paid Volunteer time off

#LI-Remote

Who We Are:
The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams.

What You’ll Do:
As a Staff Machine Learning Engineer, you will lead the development of a large-scale ML Inference Platform at Reddit.

• Lead the end-to-end design, implementation, and maintenance of a highly available, low-latency GPU-based model serving system for search, ranking, and LLMs supporting Millions of QPS.
• Design and develop ML and Generative AI systems in cloud-based production environments on Kubernetes at scale.
• Rapidly develop prototypes and develop a high-performance feature hydration and processing system as a part of the inference stack - including routing, caching, and batching.
• Lead a unified GPU model export framework to support converting trained models into optimized GPU inference models.
• Strong understanding of real-time ML observability to track feature/model performance.
• Experience working with LLM serving online at scale.
• Built an E2E inference performance benchmarking framework
• Deep Understanding of multi-cluster compute environment and network topology that is specific to ML inference use cases.

Who You Might Be:

• 7+ years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles.
• Have experience operating orchestration systems such as Kubernetes at scale
• Deep experience with cloud-based technologies for supporting an ML platform, including tools like AWS, Google Cloud Storage, infrastructure-as-code (Terraform), and more
• Proficiency with the common programming languages and frameworks of ML, such as Go, Python, etc.
• Excellent communication skills with the ability to articulate technical AI concepts to non-technical stakeholders
• Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the genAI product development lifecycle.
• Strong knowledge of model serving, inference pipelines, monitoring, and observability for AI systems is a plus
• Strong proficiency in Python and deep experience with modern AI/ML frameworks (Triton, Dynamo, vLLM, Pytorch)

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave