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

Staff Software Engineer, Backend

The Staff Engineer will work closely with AI/ML engineers, product managers, app...

Location

United States , NYC

Salary:

160000.00 - 190000.00 USD / Year

Conductor

Expiration Date

Until further notice

Requirements

Completed studies in Computer Science, Mathematics, engineering or a related field or equivalent professional experience
8+ years of experience in software development, with experience in product-driven companies
Strong expertise in system design, distributed computing, and scalable architecture patterns for handling large datasets and high-throughput applications
Proficiency in multiple programming languages with strong Python coding skills. Experience with Java is highly valued
Strong database experience including both SQL and NoSQL systems, with knowledge of data modeling and optimization techniques
Experience with AI/ML technologies including LLMs, vector databases (e.g., Milvus), embeddings, and ML frameworks
Knowledge of MLOps practices, model deployment, and AI system integration in production environments
Experience working across the full software development lifecycle including CI/CD, monitoring, testing, and production deployment
Proven track record of technical leadership, mentoring engineers, and driving engineering excellence within teams
Up-to-date with rapidly-evolving technologies and demonstrated ability to evaluate and adopt new tools and frameworks

Job Responsibility

Lead the technical architecture, design, and implementation of large-scale distributed systems and data platforms to support customer needs and business growth
Oversee the planning, execution, and successful delivery of complex engineering projects, ensuring adherence to engineering best practices and quality standards
Design and build scalable, high-performance backend systems and APIs that handle millions of requests and large datasets efficiently
Architect robust data processing pipelines and ETL workflows using modern cloud technologies and distributed computing frameworks
Drive technical decision-making across the engineering organization, evaluating trade-offs and establishing engineering standards and practices
Lead cross-functional collaboration with product, AI/ML engineering, data engineering, and infrastructure teams to deliver comprehensive solutions
Build and maintain CI/CD pipelines, monitoring systems, and deployment automation to ensure reliable software delivery
Implement AI/ML capabilities including LLM integration, vector databases, and intelligent content processing workflows
Mentor senior and junior engineers, fostering technical excellence and knowledge sharing within the engineering organization

What we offer

100% covered employee medical plan
a dental & vision plans
401(k) with employer contribution
an unlimited vacation policy
10 sick days
short-term disability
long-term disability
generous paid parental leave
employee assistance program
flexible savings accounts

Fulltime

Staff Backend Engineer

Kalepa is looking for a Staff Backend Engineer to work on its AI Copilot platfor...

Location

Salary:

145000.00 - 185000.00 USD / Year

Kalepa

Expiration Date

Until further notice

Requirements

8+ years of relevant software engineering experience
Excellent development skills including design, debugging and problem solving
Bachelors or master's degree in computer science or a related field
Experience with Python3 or other OO languages (Java, C++, C#, etc.)
Experience with AWS (EC2, Lambda, etc.) and serverless technologies
Experience with relational databases, preference for PostgreSQL
Experience working on distributed systems creating scalable, fault-tolerant infrastructure
Experience building data driven microservices leveraging RESTful API's
Experience with tools such as Docker, Git, GitHub, Flask, NumPy, Pandas

Job Responsibility

Work on advanced systems including NLP, firmographic data, entity resolution
Solve problems at the intersection of large and performant data pipelines, distributed systems, machine learning models, and robust infrastructure
Collaborate with a global team of full-stack, data, ML, and DevOps engineers
Build scalable and reliable backend solutions

What we offer

Competitive salary (based on experience level)
Significant equity options package
20 days of PTO a year
Global team offsites
Healthy living/gym stipend
Mobile phone bill stipend
Continuing education credits

Fulltime

Member of Technical Staff, Cloud Infrastructure

As a Software Engineer on our Cloud Infrastructure team, you'll be at the forefr...

Location

United States , New York, NY; San Mateo, CA; Redwood City, CA

Salary:

175000.00 - 220000.00 USD / Year

Fireworks AI

Expiration Date

Until further notice

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
5+ years of experience designing and building backend infrastructure in cloud environments (e.g., AWS, GCP, Azure)
Proven experience in ML infrastructure and tooling (e.g., PyTorch, TensorFlow, Vertex AI, SageMaker, Kubernetes, etc.)
Strong software development skills in languages like Python, or C++
Deep understanding of distributed systems fundamentals: scheduling, orchestration, storage, networking, and compute optimization

Job Responsibility

Architect and build scalable, resilient, and high-performance backend infrastructure to support distributed training, inference, and data processing pipelines
Lead technical design discussions, mentor other engineers, and establish best practices for building and operating large-scale ML infrastructure
Design and implement core backend services (e.g., job schedulers, resource managers, autoscalers, model serving layers) with a focus on efficiency and low latency
Drive infrastructure optimization initiatives, including compute cost reduction, storage lifecycle management, and network performance tuning
Collaborate cross-functionally with ML, DevOps, and product teams to translate research and product needs into robust infrastructure solutions
Continuously evaluate and integrate cloud-native and open-source technologies (e.g., Kubernetes, Ray, Kubeflow, MLFlow) to enhance our platform’s capabilities and reliability
Own end-to-end systems from design to deployment and observability, with a strong emphasis on reliability, fault tolerance, and operational excellence

What we offer

Meaningful equity in a fast-growing startup
Competitive salary
Comprehensive benefits package

Fulltime

Engineering Manager, Infrastructure

As an Engineering Manager for the Infrastructure team, you’ll lead the engineers...

Location

Canada; United States

Salary:

195000.00 - 285000.00 USD / Year

Apollo.io

Expiration Date

Until further notice

Requirements

5+ years of hands-on software or infrastructure engineering experience
2+ years of experience leading teams of senior and staff-level engineers in platform, SRE, or infrastructure domains
Proven ability to design and operate large-scale distributed systems in cloud environments (preferably GCP or AWS)
Expertise with Kubernetes, Docker, Terraform, Ubuntu, and CI/CD pipelines
Familiarity with observability tools (Grafana, Prometheus, ELK, Datadog, NewRelic) and performance tuning
Strong grounding in networking, security, and reliability principles
Experience managing infrastructure costs, availability SLAs, and high-throughput systems at scale

Job Responsibility

Lead, coach, and grow a distributed team of high-impact Infrastructure Engineers
Partner with senior engineering leadership on strategic initiatives such as cloud migration, infrastructure scaling, platform reliability, and cost efficiency
Define and implement modern operational excellence practices, including SLOs, error budgets, incident reviews, and performance monitoring
Guide technical decision-making across key areas like Kubernetes, GCP, observability, networking, CI/CD, and IaC (Terraform, Ansible)
Collaborate with AI, Data, and Product Engineering teams to ensure infrastructure scalability for ML and AI-native workloads
Run effective 1:1s, career development conversations, and quarterly performance reviews
Support recruiting efforts to attract top engineering talent across time zones

What we offer

Equity
Company bonus or sales commissions/bonuses
401(k) plan
At least 10 paid holidays per year
Flex PTO
Parental leave
Employee assistance program and wellbeing benefits
Global travel coverage
Life/AD&D/STD/LTD insurance
FSA/HSA and medical, dental, and vision benefits

Fulltime

Senior Staff Machine Learning Engineer

Help design our AI platform and develop our next generation of machine learning ...

Location

United States , San Francisco

Salary:

216500.00 - 324500.00 USD / Year

GoFundMe

Expiration Date

Until further notice

Requirements

9+ years of hands-on experience in machine learning engineering, AI development, software engineering, or related fields
Experience emphasizing secure, large-scale, distributed system design, AI/ML pipeline development, and implementation
Extensive experience designing, developing, and operating scalable backend systems
Experience applying software engineering best practices such as domain-driven design, event-driven architectures, and microservices
Deep expertise in agentic workflows, AI evaluation solutions, prompt management, and secure AI development and testing practices
Strong knowledge of relational and document-based databases, data storage paradigms, and efficient RESTful API design
Experience establishing robust CI/CD pipelines, automated testing (unit and integration), and deployment practices
Strong leadership skills, including effective planning and management of complex projects, mentoring of team members, and fostering a collaborative, high-performing engineering culture
Excellent communicator, able to articulate complex technical concepts clearly to both technical and non-technical stakeholders
Bachelor's degree in Computer Science, Software Engineering, or a related technical field (preferred)

Job Responsibility

Design and implement AI platforms to enable scalable and secure access to LLMs from multiple model providers for diverse use cases
Design and implement agentic workflows, agentic tool ecosystems, and LLM prompt management solutions
Design, build, and optimize scalable model training, fine tuning, and inference pipelines, ensuring robust integration with production systems
Influence technical strategy and approach to developing embedding stores, vector databases, and other reusable assets
Lead initiatives to streamline ML and AI workflows, improve operational efficiency, and establish standardized procedures to achieve consistent, high-quality results across our AI systems
Design and develop backend services and RESTful APIs using Python and FastAPI, integrating seamlessly with ML pipelines and services
Take operational responsibility for team-owned services, including performance monitoring, optimization, troubleshooting, and participation in an on-call rotation
Collaborate with both technical and non-technical colleagues, including data and applied scientists, software engineers, product managers, and business stakeholders, to deliver reliable and scalable ML-driven products
Coach and mentor fellow ML engineers, promoting a culture of collaboration, continuous improvement, and engineering excellence within the team
Employ a diverse set of tools and platforms including Python, AWS, Databricks, Docker, Kubernetes, FastAPI, Terraform, Snowflake, Coralogix, and GitHub to build, deploy, and maintain scalable, highly available machine learning infrastructure

What we offer

Competitive pay
Comprehensive healthcare benefits
Financial assistance for things like hybrid work, family planning
Generous parental leave
Flexible time-off policies
Mental health and wellness resources
Learning, development, and recognition programs

Fulltime

Staff Machine Learning Engineer

As a Staff Machine Learning Engineer at Aignostics, you will play a crucial role...

Location

Germany , Berlin

Salary:

Not provided

Aignostics

Expiration Date

Until further notice

Requirements

Advanced degree in a relevant field or extensive work experience
8+ years of industry experience, with at least 2 years as Staff Engineer or an equivalent role
Proven track record of driving technical excellence and innovation
Solid background in data-intensive systems and software architecture, design patterns and clean coding
Expert Python programming and fluency in C/C++ or other low-level language(s)
Experience with designing and implementing large-scale, distributed ML systems and platforms
Proven track record of deploying ML models into production environments
Strong knowledge of machine learning fundamentals
Experience with deep learning frameworks (e.g. Pytorch and Tensorflow) and state-of-the-art techniques (e.g. generative models)
Deep understanding of cloud technologies (e.g. GCP, AWS), containerization and orchestration (Kubernetes)

Job Responsibility

Define and drive the technical architecture and system design principles for our AI platform and infrastructure
Work in close collaboration with engineering leads to build flexible frameworks and systems for model training, evaluation and inference across different pathology applications
Guide the CTO office, product management and fellow engineering leads through complex decisions by providing expert consultation on feasibility, architecture, trade-offs and risk mitigation strategies, while ensuring alignment with our technical vision
Foster technical alignment across teams by establishing shared architectural principles and best practices, facilitating cross-team design reviews to enable consistent decision-making across domains
Champion technical excellence by leading strategic initiatives that modernize our architecture and reduce technical debt while measuring and improving our technical health metrics
Elevate the technical capabilities of our engineering staff through structured mentoring, workshops and establishing comprehensive technical guidelines that enable teams to make better design decisions
Drive innovation by evaluating emerging technologies, leading proof-of-concept initiatives and building support for strategic technical investments that advance our engineering capabilities while ensuring measurable business value

What we offer

Cutting-edge AI research and development, with involvement of Charité, TU Berlin and our other partners
Work with a welcoming, diverse and highly international team of colleagues
Opportunity to take responsibility and grow your role within the startup
Expand your skills by benefitting from our Learning & Development yearly budget of 1,000 € (plus 2 L&D days), language classes and internal development programs
Mentoring program, you’ll learn from great experts
Flexible working hours and teleworking policy
30 paid vacations days per year
We are family & pet friendly and support flexible parental leave options
Pick a subsidized membership of your choice among public transport, sports and well-being
Enjoy our social gatherings, lunches and off-site events for a fun and inclusive work environment

Staff MLOps Engineer

At Inworld, we’re building the AI framework behind the next generation of real-t...

Location

Canada , Vancouver

Salary:

190000.00 - 240000.00 CAD / Year

Inworld AI

Expiration Date

Until further notice

Requirements

7+ years of software engineering experience
5+ years of infrastructure-as-code
Proficiency in managing Kubernetes clusters and applications, including creating Helm charts/Kustomize manifests for new applications
Experience in creating and maintaining CI/CD pipelines for both applications and infrastructure deployments (using tools like Terraform/Terragrunt, ArgoCD, GitHub Actions, Ansible, etc.)
Deep knowledge of at least one major cloud provider (Google Cloud Platform, Microsoft Azure, Oracle Cloud)
Proficient in at least one backend programming/scripting languages such as Golang, Python, and Bash
Knowledge of SLURM or similar job schedulers for distributed training
Experience with data pipeline and workflow management tools
Desire to work at a fast-growing Series A startup, comfortable with uncertainty, owning and scaling new products, and embracing an experimental and iterative development process

Job Responsibility

Build and scale MLOps systems to streamline the end-to-end ML model lifecycle on the Inworld AI platform, from training to deployment
Design and implement robust model training, evaluation, and release pipelines
Collaborate cross-functionally with ML and backend teams to design, deploy, and maintain scalable secure infrastructure for Inworld’s AI Engine and Studio
Facilitate a "you build it, you run it" culture by providing the necessary tools and processes for monitoring the reliability, availability, and performance of services
Manage CI/CD pipelines to ensure smooth and efficient code integration and deployment
Identify and implement opportunities to enhance engineering speed and efficiency
Provide technical leadership in ML engineering best practices, raise the technical bar, and mentor junior engineers in MLOps principles

What we offer

equity
benefits

Fulltime

Staff MLOps Engineer

At Inworld, we’re building the AI framework behind the next generation of real-t...

Location

United States , Mountain View

Salary:

180000.00 - 280000.00 USD / Year

Inworld AI

Expiration Date

Until further notice

Requirements

7+ years of software engineering experience, with 5+ years of infrastructure-as-code
Proficiency in managing Kubernetes clusters and applications, including creating Helm charts/Kustomize manifests for new applications
Experience in creating and maintaining CI/CD pipelines for both applications and infrastructure deployments (using tools like Terraform/Terragrunt, ArgoCD, GitHub Actions, Ansible, etc.)
Deep knowledge of at least one major cloud provider (Google Cloud Platform, Microsoft Azure, Oracle Cloud)
Proficient in at least one backend programming/scripting languages such as Golang, Python, and Bash
Knowledge of SLURM or similar job schedulers for distributed training
Experience with data pipeline and workflow management tools
Desire to work at a fast-growing Series A startup, comfortable with uncertainty, owning and scaling new products, and embracing an experimental and iterative development process
In-office location: Mountain View, CA, United States. You must be available for hybrid work

Job Responsibility

Build and scale MLOps systems to streamline the end-to-end ML model lifecycle on the Inworld AI platform, from training to deployment
Design and implement robust model training, evaluation, and release pipelines
Collaborate cross-functionally with ML and backend teams to design, deploy, and maintain scalable secure infrastructure for Inworld’s AI Engine and Studio
Facilitate a "you build it, you run it" culture by providing the necessary tools and processes for monitoring the reliability, availability, and performance of services
Manage CI/CD pipelines to ensure smooth and efficient code integration and deployment
Identify and implement opportunities to enhance engineering speed and efficiency
Provide technical leadership in ML engineering best practices, raise the technical bar, and mentor junior engineers in MLOps principles

What we offer

equity and benefits

Fulltime

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Staff Software Engineer (Distributed Systems & ML Infrastructure)

Job Description

Job Responsibility

Requirements

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