Bengaluru, KA, India
Open 3 months, first seen by us 92 days agoWe are looking for a Staff Machine Learning Engineer to play a pivotal role within the AI team. This role goes beyond building models - you will set the technical direction and lead initiatives that push the boundaries of what's possible. 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. ResponsibilitiesRead the full posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Own end-to-end development and deployment of ranking and retrieval models at scale
Build relevance models that power recommender systems and personalized intent engines
Explore new ML ranking approaches and generative AI and NLP product features
Take ideas from conception to production with partner data science, product and infrastructure teams
Mentor junior ML engineers on entity resolution, lead scoring and search relevance
Own end-to-end model development and deployment of embeddings, retrieval, ranking, and classification models in large-scale production environments.
Build and deploy relevance models that power our various recommender systems and personalized intent engines.
Explore novel approaches for machine learning ranking and modeling downstream impact, as well as new ways of creating new product features by leveraging the cutting edge machine learning techniques in Generative AI, NLP.
Work directly with partner data science, product, and infrastructure teams to take your ideas from conception to production.
Mentor junior ML engineers in applying advanced machine learning techniques to core problems such as entity resolution, lead scoring, and search relevance.
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.
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.
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.
Open 3 monthsWe first saw this posting 92 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 92
Up longer than most. Similar jobs usually come down between day 8 and day 76.
Well past LinkedIn’s usual: its jobs come down by about day 7.
From 5,460 similar postings that came down, and 55 of LinkedIn’s. Coming down is not always a hire.
8 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 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.
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New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
We are looking for a Staff Machine Learning Engineer to play a pivotal role within the AI team. This role goes beyond building models - you will set the technical direction and lead initiatives that push the boundaries of what's possible. 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
Own end-to-end model development and deployment of embeddings, retrieval, ranking, and classification models in large-scale production environments.
Build and deploy relevance models that power our various recommender systems and personalized intent engines.
Explore novel approaches for machine learning ranking and modeling downstream impact, as well as new ways of creating new product features by leveraging the cutting edge machine learning techniques in Generative AI, NLP.
Keep scalability and performance in mind through your design and engineering choices.
Work directly with partner data science, product, and infrastructure teams to take your ideas from conception to production.
Mentor junior ML engineers in applying advanced machine learning techniques to core problems such as entity resolution, lead scoring, and search relevance.
Represent LinkedIn in academic and industry circles by showcasing our innovation, data products and scientific expertise in bringing game-changing data products to market.
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.
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 and Compliance Posters for Job Candidates
Please use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants, as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters: https://www.linkedin.com/legal/candidate-portal.
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.
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Bengaluru, KA, India
We are looking for a Staff Machine Learning Engineer to play a pivotal role within the AI team. This role goes beyond building models - you will set the technical direction and lead initiatives that push the boundaries of what's possible. 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
Global Data Privacy Notice and Compliance Posters for Job Candidates Please use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants, as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters: https://www.linkedin.com/legal/candidate-portal. Company Description