Staff Software Engineer (Distributed Systems & ML Infrastructure) Job at Hunter Bond (Paris)

Staff Software Engineer - ML Michelangelo

About the Role: Partners with stakeholders and leads team efforts to build and m...

Location

United States , Sunnyvale

Salary:

232000.00 - 258000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

Master in relevant fields (CS, EE, Math, Stats, etc.) AND 6-years full-time Software Engineering work experience in deep learning
Proficiency in Python and PyTorch
Expertise in designing, debugging, and optimizing distributed deep learning systems
Working experience of distributed training in PyTorch at Scale (e.g., data parallelism, model parallelism)
Strong ability to translate complex DL requirements and problems into scalable solutions

Job Responsibility

Partners with stakeholders and leads team efforts to build and maintain Machine Learning backend services and solutions to support user-facing products, downstream services, or infrastructure tools and platforms used across Uber
Design and build tools to empower production teams to innovate and productionize state-of-the-art deep learning models at Uber
Develop and maintain scalable, end-to-end deep learning training systems and frameworks
Ensure distributed training tools are reliable, efficient, flexible to use for new production use cases
Collaborate with cross-functional teams including machine learning engineers, backend engineers, data scientists, and data engineers to deliver robust ML solutions for Uber

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
All full-time employees are eligible to participate in a 401(k) plan
Eligible for various benefits (details at link)

Fulltime

Staff Software Engineer, Core Infrastructure

Our Core Infrastructure team in Aarhus is at the forefront of building and scali...

Location

Denmark , Aarhus

Salary:

Not provided

Uber

Expiration Date

Until further notice

Requirements

8+ years of experience in backend software development with distributed systems, infrastructure, or cloud platforms
Strong expertise in Go, Java, or similar backend languages, with a deep understanding of Kubernetes, cloud infrastructure, and high-scale systems
Experience leading cross-team or team-wide projects focused on system modernization, performance optimizations, and deployment safety improvements
Experience designing and implementing highly available, efficient, and secure cloud-native/kubernetes architectures
Deep understanding of safe deployment strategies, workload automation, and resilience engineering
Strong experience in scaling autoscaling solutions, ARM adoption, hybrid cloud, or GPU support for ML workloads
Ability to lead complex, cross-team engineering projects and build strategic relationships with stakeholders across platform, security, and infrastructure teams

Job Responsibility

Design and implement backend infrastructure components to support Uber’s growing workloads, including deployment engines, autoscalers, and hybrid cloud environments
Lead cross-team projects focused on safe deployment and rollback automation across stateless, stateful, and batch workloads, improving resilience and developer efficiency
Improve infrastructure security and compliance, including encryption-at-rest, ransomware mitigation, and cloud security best practices
Contribute to and drive modernization efforts within the team and across related teams, including Kubernetes migration, unified workload platforms, and PaaS improvements
Optimize Uber’s infrastructure efficiency, focusing on ARM adoption, autoscaling enhancements, and cost-effective compute allocation
Proactively mentor other engineers and help define the technical direction for your team, ensuring Uber’s backend infrastructure remains reliable, scalable, and efficient

Fulltime

Staff Software Engineer, GPU Infrastructure (HPC)

The internal infrastructure team is responsible for building world-class infrast...

Location

Salary:

Not provided

Cohere

Expiration Date

Until further notice

Requirements

Deep expertise in ML/HPC infrastructure: Experience with GPU/TPU clusters, distributed training frameworks (JAX, PyTorch, TensorFlow), and high-performance computing (HPC) environments
Kubernetes at scale: Proven ability to deploy, manage, and troubleshoot cloud-native Kubernetes clusters for AI workloads
Strong programming skills: Proficiency in Python (for ML tooling) and Go (for systems engineering), with a preference for open-source contributions over reinventing solutions
Low-level systems knowledge: Familiarity with Linux internals, RDMA networking, and performance optimization for ML workloads
Research collaboration experience: A track record of working closely with AI researchers or ML engineers to solve infrastructure challenges
Self-directed problem-solving: The ability to identify bottlenecks, propose solutions, and drive impact in a fast-paced environment

Job Responsibility

Build and scale ML-optimized HPC infrastructure: Deploy and manage Kubernetes-based GPU/TPU superclusters across multiple clouds, ensuring high throughput and low-latency performance for AI workloads
Optimize for AI/ML training: Collaborate with cloud providers to fine-tune infrastructure for cost efficiency, reliability, and performance, leveraging technologies like RDMA, NCCL, and high-speed interconnects
Troubleshoot and resolve complex issues: Proactively identify and resolve infrastructure bottlenecks, performance degradation, and system failures to ensure minimal disruption to AI/ML workflows
Enable researchers with self-service tools: Design intuitive interfaces and workflows that allow researchers to monitor, debug, and optimize their training jobs independently
Drive innovation in ML infrastructure: Work closely with AI researchers to understand emerging needs (e.g., JAX, PyTorch, distributed training) and translate them into robust, scalable infrastructure solutions
Champion best practices: Advocate for observability, automation, and infrastructure-as-code (IaC) across the organization, ensuring systems are maintainable and resilient
Mentorship and collaboration: Share expertise through code reviews, documentation, and cross-team collaboration, fostering a culture of knowledge transfer and engineering excellence

What we offer

An open and inclusive culture and work environment
Work closely with a team on the cutting edge of AI research
Weekly lunch stipend, in-office lunches & snacks
Full health and dental benefits, including a separate budget to take care of your mental health
100% Parental Leave top-up for up to 6 months
Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
6 weeks of vacation (30 working days!)

Fulltime

Staff Machine Learning Engineer - ML Training Infrastructure

The Role:   We are seeking an experienced, technically strong, impact-driven ex...

Location

United States , Austin; Mountain View

Salary:

185000.00 - 335300.00 USD / Year

General Motors

Expiration Date

Until further notice

Requirements

Bachelor's degree or higher in Computer Science or a related field, or equivalent practical experience
8+ years of professional software engineering experience
5+ years of specialized experience in AI/ML infrastructure, such as enabling distributed training for large-scale ML models
Strong programming skills in Python, with deep proficiency in frameworks such as PyTorch (preferred), TensorFlow, or similar ML systems
Proven experience designing and operating distributed systems for ML training, including distributed computing, GPU computing, and cloud environments (AWS, GCP, Azure)
Demonstrated track record of leading technically ambiguous, cross-team infrastructure initiatives and driving them to measurable impact
Strong architectural judgment and ability to make sound technical tradeoffs across performance, reliability, usability, and cost
Willingness to travel to Sunnyvale, CA as needed
Comfortable operating in highly ambiguous and dynamic environments

Job Responsibility

Define and drive the architecture, design, and development of scalable, reliable, and high-performance ML frameworks and platform capabilities to support model training at scale
Lead model training performance analysis and optimization efforts across distributed training workflows, improving scalability, efficiency, and cost across heterogeneous hardware environments
Raise the bar on system observability, debuggability, operational excellence, and developer experience across the ML training stack
Own large, ambiguous, cross-functional technical initiatives from strategy through execution, including technical roadmap definition, tradeoff analysis, and delivery
Influence platform direction by identifying long-term infrastructure investments, setting engineering standards, and driving adoption of best practices across teams
Collaborate across organizational boundaries to align requirements, resolve technical disagreements, and integrate new capabilities into the platform ecosystem
Mentor engineers through design reviews, technical guidance, and hands-on partnership, while elevating engineering quality across the team

What we offer

medical
dental
vision
Health Savings Account
Flexible Spending Accounts
retirement savings plan
sickness and accident benefits
life insurance
paid vacation & holidays
tuition assistance programs

Fulltime

Staff Software Engineer- Earner Offer Experience

Location

United States , San Francisco; Sunnyvale

Salary:

232000.00 - 258000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
8+ years of professional software development experience, with a deep focus on backend systems and distributed architectures
Expertise in building scalable, resilient services using technologies such as Go, Java, or Python
Strong understanding of system design, data modeling, and performance tuning
Experience driving large-scale initiatives from inception to delivery across multiple teams or functions

Job Responsibility

Lead by Influence: Set the technical vision and roadmap for core systems that power personalized offer delivery and earner engagement
Architect Systems: Design and evolve backend systems to be scalable, reliable, and flexible enough to support future innovations
Drive Cross-Org Impact: Partner closely with platform, data, ML, and product teams across Uber to ensure cohesive and performant system design
Uphold Engineering Excellence: Champion high standards for design, code quality, testing, and operational excellence
Mentor and Uplift: Guide engineers across multiple teams, offering technical mentorship and fostering a culture of growth and accountability
Own Delivery: Take full ownership of projects from concept to production, ensuring timely execution and measurable impact
Advance Innovation: Identify technical opportunities and lead the charge in tackling complex infrastructure and product challenges using data-driven decision making

What we offer

bonus program
equity award & other types of comp
401(k) plan
various benefits

Fulltime

Senior Staff Software Engineer (Search)

We are on a mission to build a reliable, fast, and scalable search for DoorDash....

Location

United States , San Francisco, CA; Sunnyvale, CA; Seattle, WA

Salary:

231200.00 - 340000.00 USD / Year

DoorDash

Expiration Date

Until further notice

Requirements

B.S. or M.S. in Computer Science or equivalent
10+ years of industry experience, with a track record of leading large-scale, high-impact components and systems
Proven ability to drive multi-quarter technical roadmaps as a technical lead, with clear ownership of architectural decisions
Deep expertise in distributed systems and data pipelines at scale. Expertise in search infrastructure, including indexing and serving stack
Strong understanding of ML systems, embedding-based retrieval, model serving tradeoffs, and multi-stage ranking architectures
Strong technical intuition paired with the ability to influence and align cross-functional stakeholders
Humility and growth mindset, leading through expertise and collaboration, not hierarchy

Job Responsibility

Lead at scale: Serve as the uber tech lead for Search, providing technical vision and architectural direction across the entire organization. Own a multi-year roadmap that spans multiple services and teams powering mission-critical products at DoorDash
Architect the next-generation search stack: Drive the rebuild of core search infrastructure, including indexing pipelines, embedding-based retrieval, and ML ranker serving in latency-sensitive paths. This stack will power both consumer search and agentic commerce experiences at DoorDash scale
Influence across teams: Drive alignment across ML, Infrastructure, Product, and partner engineering teams. Mentor staff and senior engineers across the search org to raise the bar of technical excellence
Shape engineering culture: Set the technical bar for how the search org designs, ships, and operates large-scale systems, and define the patterns that will outlast any single project
Hands-on problem solving: Dig into complex distributed systems challenges, from low-latency serving to indexing freshness tradeoffs, and write code that moves the needle

What we offer

401(k) plan with employer matching
16 weeks of paid parental leave
wellness benefits
commuter benefits match
paid time off and paid sick leave in compliance with applicable laws
medical, dental, and vision benefits
11 paid holidays
disability and basic life insurance
family-forming assistance
mental health program

Fulltime

Staff Software Engineer - Backend Gen Ai

The Media Platform team builds Uber's unified, scalable infrastructure for inges...

Location

United States , Sunnyvale

Salary:

232000.00 - 258000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

10+ years of backend engineering experience, with deep expertise in distributed systems and large-scale service architecture
Strong backend engineering experience (Go, Java, C++, or similar) with expertise in system design, performance optimization, and reliability
Experience building high-throughput, low-latency services handling large data volumes (streaming, storage, or media systems)

Job Responsibility

Architect and scale distributed backend systems that support media ingestion, processing, intelligence, and delivery across global regions
Improve performance, reliability, and cost efficiency of high-throughput media pipelines
Design infrastructure that enables efficient integration and execution of ML inference workloads within media systems
Drive technical strategy and long-term architectural decisions across the Media Platform
Mentor engineers and raise the bar for engineering excellence, operational rigor, and system design

What we offer

Bonus program
Equity award
401(k) plan
Various benefits

Fulltime

Staff Software Engineer, Search

As a Staff Software Engineer, you will help make SiriusXM’s massive content cata...

Location

United States , Texas; Georgia; New Jersey; New York

Salary:

101500.00 - 195000.00 USD / Year

SiriusXM

Expiration Date

Until further notice

Requirements

7+ years of professional software engineering experience building large-scale backend systems in Java, building backend microservices and scalable distributed systems
3+ years of experience with Python
Deep experience with search frameworks, metadata indexing, and retrieval systems
Proven experience leading complex, cross-functional technical initiatives
Expert-level experience with AWS, including deploying applications using services such as EC2, Lambda, S3, DynamoDB, CloudWatch, ElastiCache, and IAM
Strong foundation in object-oriented design, system design, and design patterns
Proven ability to make sound architectural trade-offs while maintaining long-term extensibility
Comfort working across system boundaries (infrastructure, ML, and adjacent service domains)
Ability to handle multiple tasks in a fast-paced environment
Excellent interpersonal and communication skills

Job Responsibility

Design, build, and operate well-architected, scalable microservices for the search services stack
Drive architectural evolution of indexing, retrieval, and serving pipelines from prototype to production
Evaluate, fine-tune, and integrate off-the-shelf LLM models, rapidly prototyping where needed
Drive cross-functional initiatives, collaborating with product, science, design, and infrastructure partners
Act as a strong technical bridge between science/ML and engineering teams
Partner with the Voice Search team to eliminate redundancies and enhance the overall search ecosystem
Influence and uphold engineering best practices, mentoring other engineers as the team scales

Fulltime

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Staff Software Engineer (Distributed Systems & ML Infrastructure)

Job Description

Job Responsibility

Requirements

What we offer

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