Machine Learning Engineering Manager, Moveworks
GAI Search Ranking
$275-330k
Equity for all full time roles
Office located in Mountain View, CA
Enterprise-built conversational AI platform
Be an early applicant
Enterprise-built conversational AI platform
501-1000 employees
Be an early applicant
$275-330k
Equity for all full time roles
Office located in Mountain View, CA
501-1000 employees
Company mission
To make getting instant help at work effortless for employees.
Role
Who you are
- Master's degree in Computer Science specializing in Machine Learning or a related field. A Ph.D. is a plus
- 8+ years of experience in applied machine learning preferably in the ranking/relevance domain, including 3+ years in technical leadership or management roles
- Proven technical expertise that has been recognized at Staff Engineer (comparable to Google/Meta L6) or above level
- Proven experience managing high-performing teams, including mentoring and supporting Staff-level (I6) or higher engineers, with a strong track record of delivering technically ambitious, production-grade projects
- Proficiency in programming languages such as Python, Golang, C++
- Excellent problem-solving and analytical skills
- Strong communication skills
- Knowledge of software engineering best practices and experience with deploying machine learning models in production environments
What the job involves
- As the leader of a team of talented search relevance engineers, your objective will be to measure and improve the ranking and relevance of our AI-powered enterprise search applications. Since these applications also leverage large language models (LLMs), you will also be responsible for measuring and improving RAG-based objectives such as summarization, groundedness of responses, and citation correctness and completeness
- You will guide the team to drive end-to-end development of machine-learning models, including data synthesis, feature engineering, experiment design, evaluation and more
- Your team will play a pivotal role in improving our search relevance in a systematic and methodical manner as we scale to new customers, new types of data and use-cases, and will ultimately be accountable for the ranking quality of all our enterprise search products
- Your team's ownership of search quality is crucial to the company's search product lines, with success measured by its enablement capabilities. You will enable your team members by facilitating rapid iteration on model enhancements, allowing them to improve ML metrics with a clear understanding of performance tradeoffs and generalizability
- You will be responsible for guiding the team's technical direction, managing project timelines, and ensuring the robustness, efficiency, and innovation of our machine learning based search systems
- Your team will collaborate closely with search infrastructure and platform engineers, and partner with product, design, and customer success teams to jointly achieve business objectives
- Team Leadership:
- Recruit, hire, and mentor a high-performing team of machine learning engineers
- Maintain a “ranking and relevance” mindset in your team, developing a thought leadership on our long-term relevance roadmap
- Foster a collaborative and inclusive team culture, promoting knowledge sharing and continuous learning
- Set clear goals, provide regular feedback, and promote professional growth and development of team members
- Project Management:
- Develop and manage project plans, timelines, and budgets for machine learning initiatives
- Ensure the successful execution of projects, from ideation and prototyping to production deployment
- Collaborate with cross-functional teams to define project requirements and priorities
- Technical Leadership:
- Drive the technical vision and strategy
- Guide the integration and application of large language models (LLMs) and retrieval-augmented generation (RAG) techniques to enable modern, intelligent search experiences
- Oversee the research, development, and deployment of machine learning models and algorithms
- Stay current with the latest advancements in the field and ensure that our projects leverage cutting-edge technologies
- Quality and Performance:
- Implement best practices for model development, data pipelines, and model evaluation
- Monitor and optimize the performance, scalability, and reliability of machine learning systems
- Ensure that our AI solutions meet high standards of accuracy and efficiency
- Stakeholder Communication:
- Collaborate with leadership, product managers, customer success staff, and other teams to align machine learning initiatives with business goals
- Provide regular updates and reports on project status, challenges, and successes to stakeholders
- Communicate, collaborate, and build relationships with partner teams and peer teams to facilitate cross-functional projects
Our take
Moveworks provides IT service and helpdesk support through an AI-driven chatbot. Its system utilizes information about an employee, such as their role and seniority level, to deliver the correct information or carry out processes. Moveworks claims to solve 30% of IT support tickets within weeks of implementation.
In 2024, Moveworks opened a data center in Australia and its service has seen strong uptake from large enterprise-level companies, where IT teams deal with hundreds of requests at a time, helping to minimize backlog and gain back employee time. As more and more workers move from office to home or hybrid, IT support requests have boomed, opening up the opportunity for Moveworks to expand its client pool and provide solutions to help with this change.
Competitors such as Electric offer similar automated IT support services, but Moveworks has invested heavily into creating an AI system that is conversational and easy to use. Automated solutions with machine learning capabilities can also identify cost-saving opportunities. When unused software licenses are estimated to cost companies billions of dollars a year, there is money to be made by identifying and removing these avoidable costs through AI.
Steph
Company Specialist at Welcome to the Jungle
Insights
97% employee growth in 12 months
Company
Funding (last 2 of 3 rounds)
Jun 2021
$200m
SERIES C
Nov 2019
$75m
SERIES B
Total funding: $305m
Company benefits
- Fully paid medical, dental, and vision coverage with no premiums
- Fully paid short-term disability, long-term disability, and life insurance
- Free daily meals
- Unlimited PTO
- Unlimited paid sick days
- 16 weeks of 100% paid parental leave
- Medical, family care, and military leave
- Competitive salary — we’re one of the best-paying companies in the Bay Area
- 401(k) with matching
- Equity and stock options
- Commuter and parking benefits
Company HQ
Mountain View, CA
Leadership
Bhavin Shah
(CEO)After an MA at Stanford, Bhavin worked as a Director at LeapFrog Enterprises before co-founding Gazillion after 5 years in 2005. They left their CEO role at Refresh to co-found Moveworks in June 2016.
Vaibhav Nivargi
(CTO)Vaibhav started their career as a Stanford University Research Scientist before working for Aster Data as a Software Engineer. Having started ClearStory Data in 2011, they co-founded Moveworks in 2016.
Varun Singh
(President)Varun worked for half a decade as SVP of Product at Sefaira before spending 2 years as Lead Product Manager at Facebook. They left in 2016 to co-found Moveworks.
Jiang Chen
(CTO of AI)Jiang took a PhD at Yale in Computer Science before working as a Columbia Research Scientist and spending 7 years at Yahoo! and Google. After a year at Airbnb, they co-founded Moveworks.
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