Sr. Staff Software Engineer, Machine Learning at LinkedIn

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

07 Jul, 26

Salary

0.0

Posted On

08 Apr, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Large Language Models, Generative AI, Search, Recommendation Systems, Reinforcement Learning, Deep Learning, Python, Java, C++, Technical Leadership, System Architecture, Data Pipelines, Model Evaluation, Cross-functional Collaboration, Mentorship

Industry

Software Development

Description

Company Description LinkedIn is the world’s 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. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed. Join us to transform the way the world works. Job Description We are looking for a Senior Staff Machine Learning Engineer to play a pivotal role as a technical leader within the 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 large-scale machine learning systems across areas such as ranking, recommendation systems, personalization, generative AI, reinforcement learning, and large language models. Define and drive the technical roadmap and architecture for end-to-end AI systems, ensuring scalability, performance, reliability, and maintainability. Research, fine-tune, and adapt large language models (LLMs) and build and productionize advanced AI solutions, including foundation models and agentic systems, capable of reasoning, decision-making, and contextual intelligence. Drive best practices in experimentation, model evaluation, fairness, explainability, and system robustness. 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. 12+ years of experience in machine learning, artificial intelligence, or related fields. 8+ 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 15+ 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. 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: IC5/10 Department: Engineering

Responsibilities

Lead the design, development, and deployment of large-scale machine learning systems including ranking, recommendation, and generative AI. Define the technical roadmap and architecture while mentoring engineers to foster a culture of technical excellence.