JOB DETAILS

Staff Software Engineer, Machine Learning

CompanyLinkedIn
LocationBengaluru
Work ModeOn Site
PostedApril 3, 2026
About The Company
Founded in 2003, LinkedIn connects the world's professionals to make them more productive and successful. With more than 1 billion members worldwide, including executives from every Fortune 500 company, LinkedIn is the world's largest professional network. The company has a diversified business model with revenue coming from Talent Solutions, Marketing Solutions, Sales Solutions and Premium Subscriptions products. Headquartered in Silicon Valley, LinkedIn has offices across the globe.
About the Role

Company Description

LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed.

Job Description

We are looking for a Staff Machine Learning Engineer to play a pivotal role as a technical leader within the LSS AI team. This role goes beyond building models- you will set the technical direction, own the AI roadmap, and lead initiatives that push the boundaries of what's possible in enterprise AI. You will combine deep research expertise with the ability to build production-grade ML systems at scale, partnering across engineering, product, and research to deliver transformative AI solutions.

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.

Responsibilities

  • Lead the design, development, and deployment of state-of-the-art ML systems across search, recommendations, generative AI, reinforcement learning, and LLMs for Sales Navigator.
  • Define and drive the technical roadmap and architecture for end-to-end AI systems within LSS, ensuring scalability, reliability, and innovation.
  • Research, fine-tune, and adapt large language models (LLMs) and build agentic AI systems that enable reasoning, planning, and decision-making for sales professionals.
  • Partner with product, design, and other engineering teams to align AI solutions with business strategy and maximize impact.
  • Drive cross-functional collaborations with horizontal AI and platform teams to leverage foundational tools and scale adoption of innovations across LinkedIn.
  • Mentor and guide engineers, fostering a culture of craftsmanship, innovation, and technical excellence.
  • Represent LinkedIn in external venues (papers, conferences, workshops) by showcasing advances in applied AI research and engineering.

Qualifications

Basic Qualifications

  • MS/PhD degree in Computer Science or related technical discipline, or equivalent practical experience.
  • 8+ years of experience in machine learning, artificial intelligence, or related fields.
  • 5+ years in an architect or technical leadership role driving large-scale AI initiatives.
  • Hands-on experience with end-to-end ML lifecycle: data pipelines, training, deployment, monitoring, and optimization.
  • Expertise in at least one of: LLMs, generative AI, search/recommendations, reinforcement learning, or large-scale deep learning.

Preferred Qualifications

  • 10+ years of experience building and scaling machine learning systems in production.
  • Proven experience in pre-training and fine-tuning LLMs, including domain-specific adaptations.
  • Strong software engineering skills (Python, Java, C++, or similar), with the ability to design robust, scalable systems.
  • Track record of influencing product and technical strategy through AI/ML innovation.
  • Publications, patents, or open-source contributions in machine learning, NLP, or related areas.

Suggested Skills

  • Machine Learning
  • Large Language Models
  • Generative AI
  • Search & Recommendations
  • Reinforcement Learning
  • Technical Leadership
  • Cross-Functional Collaboration

You Will Benefit from Our Culture

We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.

Additional Information

India Disability Policy 

LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit https://legal.linkedin.com/content/dam/legal/Policy_India_EqualOppPWD_9-12-2023.pdf

Global Data Privacy Notice for Job Candidates ​

Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.

  • Workplace Type: Hybrid
  • Career Track & Grade: IC4/9
  • Department: Engineering
  • Key Skills
    Machine LearningLarge Language ModelsGenerative AISearch & RecommendationsReinforcement LearningTechnical LeadershipCross-Functional CollaborationPythonJavaC++System ArchitectureData PipelinesModel DeploymentAgentic AIDeep Learning
    Categories
    SoftwareTechnologyEngineeringData & AnalyticsScience & Research
    Benefits
    Health and wellness programsTime away
    Job Information
    📋Core Responsibilities
    Lead the design, development, and deployment of advanced machine learning systems including generative AI and LLMs for Sales Navigator. Define the technical roadmap and architecture while mentoring engineers to foster a culture of technical excellence.
    📋Job Type
    full time
    📊Experience Level
    10+
    💼Company Size
    23848
    📊Visa Sponsorship
    No
    💼Language
    English
    🏢Working Hours
    40 hours
    Apply Now →

    You'll be redirected to
    the company's application page