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Software Engineer, Machine Learning

Sunnyvale, California, United StatesHybridFull TimeEntry-level (exp-based)$114,000–$189,000 /yrPosted 2 months agoVisa sponsorship available

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Role summary

LinkedIn is seeking a Machine Learning Engineer to join their Auto Eval team, focusing on developing and deploying AI evaluation frameworks. This hybrid role involves building and deploying relevance models for recommender systems and intent engines, exploring cutting-edge ML techniques like Generative AI and NLP, and analyzing big data to understand member preferences. The engineer will work from ideation to production, collaborating with data science, product, and infrastructure teams. The position requires a Bachelor's degree or equivalent experience, with at least 1 year of experience in machine learning, software design, and programming languages like Python or Java.

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

Hiring Team Description

The Auto Eval team is pioneering scalable, high-fidelity evaluation frameworks for AI systems at LinkedIn. By integrating human annotation with automated evaluation pipelines, the team enables rapid, reliable assessments of AI products across domains like hiring, feed relevance, and trust. Their platform, the Auto-Eval Playground, empowers product teams to orchestrate evaluations, fine-tune prompts, and benchmark model performance with minimal overhead.

Job Description

This role will be based in Sunnyvale, San Francisco, or New York City. 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.

LinkedIn's Machine Learning Engineers are both data/research scientists and software engineers, who develop and implement machine learning models and algorithms. Unlike other companies that separate these roles, our engineers work on projects from ideation to implementation.

Responsibilities

  • Building and deploying relevance models that power our various recommender systems and personalized intent engines
  • Keeping scalability and performance in mind through your design and engineering choices.
  • You will 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.
  • You will work with big data and analyze tracking data to understand member preferences and identify opportunities for taking the products you work on to the next level.
  • You will work directly with partner data science, product, and infrastructure teams to take your ideas from conception to production.

Qualifications

Basic Qualifications

  • Bachelor's degree in Computer Science or related technical field or equivalent technical experience
  • 1+ years experience with machine learning, data mining, and information retrieval or natural language processing
  • 1+ year of industry experience in software design, development, and algorithm related solutions.
  • 1+ years experience in programming languages such as Java, Python, etc.

Preferred Qualifications{{:}}

  • 1+ years of relevant work experience
  • MS or PhD in Computer Science or related technical discipline
  • Experience developing large scale systems
  • Knowledge of recommendation systems
  • Ability to diagnose technical problems, debug code, and automate routine tasks
  • Analytical approach coupled with solid communication skills and a sense of ownership

Suggested Skills

  • Data Mining
  • Data Coding
  • Machine Learning

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. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $114,000 - $189,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https{{:}}//careers.linkedin.com/benefits.

Additional Information

Equal Opportunity Statement

We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.

If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation.

Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to{{:}}

  • Documents in alternate formats or read aloud to you
  • Having interviews in an accessible location
  • Being accompanied by a service dog
  • Having a sign language interpreter present for the interview

A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.

LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.

San Francisco Fair Chance Ordinance ​

Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.

Pay Transparency Policy Statement ​

As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link{{:}} https{{:}}//lnkd.in/paytransparency.

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.

Sample LinkedIn interview questions

  • 1

    Design and implement a ranked cache system

    system designmedium
  • 2

    What happens behind the scenes when you visit a Bitly URL in your web browser?

    system designmedium
  • 3

    Design typeahead autocomplete for person search in Linkedin

    system designmedium
  • 4

    Given an nxn grid of 1s and 0s, return the number of islands in the input

    codingmedium
  • 5

    Merge k sorted linked lists

    codinghard

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