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About This Role
Who we are
Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale.
Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video\-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term.
About the role:
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Samsara’s People team is seeking a technically skilled builder to lead the development, implementation, and maintenance of the tools and systems that power our HR workflows and AI initiatives.
Our People team helps support Samsara by providing accessible, business\-oriented HR guidance—achieved through creative problem\-solving, excellence in execution, and ethical, empathetic partnership across the company. We cover many areas, from talent acquisition and onboarding to performance management, total rewards, employee relations, workforce planning, and everything in between, and we are powered by an innovative HR operations function that is focused on reimagining how people work gets done. We value intensity, pace, and curiosity—moving quickly to deliver clear, practical solutions while continuously improving how we support the business.
This Staff AI Engineer role sits directly within the People team and acts as the technical bridge between HR professionals, people operations, program managers and the people that build Samsara, You’ll design, develop, and operate secure, scalable applications, automations, and AI workflows that transform manual HR work into efficient, production\-grade solutions. If you’re passionate about applying technology and AI to solve complex challenges and scale a modern people function, this is a unique opportunity to make a direct, measurable impact across People and the broader business.
This role is open to candidates residing in the US except the San Francisco Bay Metro Area, NYC Metro Area, and Washington, D.C. Metro Area.
You should apply if:
- You want to impact the industries that run our world: Your efforts will result in real\-world impact – helping to keep the lights on, get food into grocery stores, reduce emissions, and most importantly, ensure workers return home safely.
- You are the architect of your own career: If you put in the work, this role won’t be your last at Samsara. We set up our employees for success and have built a culture that encourages rapid career development, countless opportunities to experiment and master your craft in a hyper growth environment.
- You’re energized by our opportunity: The vision we have to digitize large sectors of the global economy requires your full focus and best efforts to bring forth creative, ambitious ideas for our customers.
- You want to be with the best: At Samsara, we win together, celebrate together and support each other. You will be surrounded by a high\-calibre team that will encourage you to do your best.
In this role, you will:
- Partner with People team members and cross\-functional stakeholders (including IT and others) to design, build, and maintain HR tech solutions that enhance how we deliver people programs to the business, streamline HR workflows, improve data quality, and drive measurable productivity gains.
- Act as a key voice in roadmap planning, experimentation frameworks, and modeling strategy discussions.
- Identify gaps in data, tools, and processes — and lead initiatives to close them.
- Develop and deploy AI\-powered tools and automations that transform core HR processes, such as employee self\-service and HR intake, onboarding and offboarding, knowledge retrieval, workforce and headcount planning, performance and talent management, total rewards analysis, and document drafting, analysis, and translation.
- Integrate people systems with core enterprise platforms (e.g., Workday, Google Suite, Slack, Salesforce, Greenhouse, and others) to ensure seamless data flow, scalability, and reliability.
- Evaluate and implement emerging technologies, staying current on advancements in AI, automation, and HR technology – and proactively identifying opportunities for innovation and efficiency.
- Enable and support end users—both People team members and employees across the business—through documentation, training, technical support, and troubleshooting to ensure adoption and smooth operation of all HR tech systems.
- Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices.
Minimum requirements for the role:
- Bachelor’s degree or comparable work experience.
- 8\+ years of relevant experience with building and scaling production\-grade enterprise applications and integrations, with strong software engineering fundamentals and the ability to independently design and deliver solutions with little or no technical guidance.
- Hands\-on experience with large language model (LLM) applications, including prompt engineering, retrieval\-augmented generation, and related AI workflows.
- Proficiency in coding in Python, particularly for scripting, data manipulation, and interacting with APIs.
- Experience with SQL or NoSQL databases, including data modeling and query optimization.
- Proficiency with low\-code / no\-code automation platforms (e.g., Workato, UiPath, Zapier, etc.), core enterprise platforms (e.g., Workday, Google Suite, Slack, Salesforce, ServiceNow, and others), AWS and similar platforms, and data warehouses (e.g., Databricks, Snowflake, Google BigQuery, Amazon Redshift).
- Strong problem\-solving mindset and curiosity about how technology, especially AI, can improve HR processes.
- Excellent collaboration and communication skills with both technical and non\-technical stakeholders.
- Ability to translate complex business workflows into scalable, reliable technical solutions, delivering iterative improvements with measurable outcomes.
- Based in Bangalore, India.
An ideal candidate also has:
- Strong product mindset with the ability to navigate ambiguity and deliver results in fast\-paced, cross\-functional environments.
- Experience working with HR technology or adjacent platforms such as HRIS, talent management, workforce planning, recruiting, and compensation tools (e.g., Workday, Greenhouse, Pave, Lattice, BritghtHire, GitHub, Cursor, etc.).
- Understanding of enterprise security, privacy, and data governance principles and how they apply to people systems and workflows—including sensitivity to handling employee data.
- Experience with fine\-tuning smaller language models or a deep understanding of model evaluation techniques beyond prompt engineering.
The range of annual base salary for full\-time employees for this position is below. Please note that base pay offered may vary depending on factors including your city of residence, job\-related knowledge, skills, and experience. This role is also eligible for an initial RSU grant with no vesting cliff, and ongoing refresh opportunities tied to performance, subject to plan terms and conditions. Learn more about our total rewards and benefits below.
Annual Base Salary
$146,370—$221,400 USDTotal Rewards
At Samsara, we build for the people who keep the global economy moving. We want owners, not passengers, which is why our rewards are designed to fuel high\-impact builders. Our compensation program delivers above\-market total compensation through a combination of base salary, performance\-based bonus/variable pay, and equity (for eligible roles) in a high\-growth public company. We meaningfully differentiate pay for our top performers, who have the opportunity to earn above\-market compensation that can outpace the broader market over time.
Beyond compensation, we provide the foundations that enable long\-term success: a flexible, employee\-led remote model, a professional development stipend, comprehensive health and parental leave plans, and more. If you’re ready to build for the long term and own the outcome, your journey starts here.
Flexible Working
At Samsara, we embrace a flexible working model that caters to the diverse needs of our teams. Our offices are open for those who prefer to work in\-person and we also support remote work where it aligns with our operational requirements. For certain positions, being close to one of our offices or within a specific geographic area is important to facilitate collaboration, access to resources, or alignment with our service regions. In these cases, the job description will clearly indicate any working location requirements. Our goal is to ensure that all members of our team can contribute effectively, whether they are working on\-site, in a hybrid model, or fully remotely. All offers of employment are contingent upon an individual’s ability to secure and maintain the legal right to work at the company and in the specified work location, if applicable.
Belonging at Samsara
At Samsara, we welcome everyone regardless of their background. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender, gender identity, sexual orientation, protected veteran status, disability, age, and other characteristics protected by law. We depend on the unique approaches of our team members to help us solve complex problems and want to ensure that Samsara is a place where people from all backgrounds can make an impact.
Accommodations
Samsara is an inclusive work environment, and we are committed to ensuring equal opportunity in employment for qualified persons with disabilities. Please email [email protected] if you require any reasonable accommodations throughout the recruiting process.
Our Commitment to Authenticity
We use Tofu, a fraud detection tool, to validate the authenticity of applications and protect against identity fraud. This ensures we are connecting with real people and allows us to prioritize genuine candidates. Please see Samsara’s Candidate Privacy Notice
Fraudulent Employment Offers
Samsara is aware of scams involving fake job interviews and offers. Please know we do not charge fees to applicants at any stage of the hiring process. Official communication about your application will only come from emails ending in @samsara.com, @us\-greenhouse\-mail.io or @mail3\.guide.co.
Salary Context
This $146K-$221K range is above the median for AI/ML Engineer roles in our dataset (median: $181K across 1996 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,824 AI roles we're tracking, AI/ML Engineer positions make up 71% of the market. At Samsara, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $178,940 based on 11,900 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $160,000. Disclosed range: $146K to $221K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
Samsara AI Hiring
Samsara has 3 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer. Positions span Seattle, WA, US, New York, NY, US, San Francisco, CA, US. Compensation range: $214K - $221K.
Location Context
AI roles in Seattle pay a median of $228,000 across 1,009 tracked positions. That's 14% above the national median.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (119) are outnumbered by mid-level (1,813) and senior (1,472) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,000. Top-quartile roles start at $253,000, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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