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Staff Software Engineer, Machine Learning

Bengaluru, KA, India

Pay
Pay not listed
Work setting
Hybrid stated · location limits — work setting source
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
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Employment
Full-time — employment source
Employment type in the employer’s listing: Full-time
From the employer’s posting
Apply at LinkedIn

What you’ll work on

Full 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

From the employer’s posting
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.

What you’ll bring

All qualifications

Core 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 experience

  • 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.
Qualification wording
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.
Education & alternatives
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.

Tools in this posting

  • C++
  • Java
  • Python
Source — Tool mentions in context
- 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.

Posting record

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Live
First seen by us
Aug 13, 2026 · 70 days ago
Recorded sightings
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Last seen by us
Oct 22, 2026

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Job description

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Job Description

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.

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.

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.

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.

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Location & working pattern

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
Work authorization
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

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