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Machine Learning Engineer - Foundational Models
Lensa
United States
Remote
USD 131,000 - 194,000
Full time
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Job summary
Lensa is seeking a Senior Machine Learning Engineer to join their team in a fully remote role. You'll drive the development and optimization of machine learning systems that enhance the personalization experience for users. The ideal candidate will have a strong background in ML, experience with real-time systems, and proficiency in Python, PyTorch, or TensorFlow. As part of a collaborative team culture, you will make significant contributions to transformative projects at Lensa.
Benefits
Qualifications
- Experienced in building, deploying, and maintaining scalable ML systems.
- Familiar with supervised learning, recommendation systems, or deep learning.
- Ability to communicate and collaborate with cross-functional teams.
Responsibilities
- Developing and productionizing machine learning models.
- Collaborating with data scientists and partners for enhanced ML capabilities.
- Improving infrastructure for next-generation recommendation systems.
Skills
Tools
Job description
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Machine Learning Engineer - Foundational Models at Stitch Fix (View all jobs) (https://www.stitchfix.com/careers/jobs)
Remote, USA
About Stitch Fix, Inc.
Stitch Fix (NASDAQ: SFIX) is the leading online personal styling service that helps people discover the styles they will love that fit perfectly so they always look - and feel - their best. Few things are more personal than getting dressed, but finding clothing that fits and looks great can be a challenge. Stitch Fix solves that problem. By pairing expert stylists with best-in-class AI and recommendation algorithms, the company leverages its assortment of exclusive and national brands to meet each client's individual tastes and needs, making it convenient for clients to express their personal style without having to spend hours in stores or sifting through endless choices online. Stitch Fix, which was founded in 2011, is headquartered in San Francisco.
About the Team
At Stitch Fix, our data science teams combine machine learning algorithms with expert human judgment to deliver personalized recommendations, transforming how clients discover their preferred styles. The Foundational Models team focuses on developing the core recommender system, which not only personalizes the client experience but also informs merchandising strategies. The team’s goal is to enhance business outcomes by improving model performance while ensuring optimal latency, uptime, and cost efficiency. Additionally, the team collaborates closely with partner teams to refine feedback mechanisms and playback initiatives.
About the Role
In this role, you will be building the next generation ML systems that transform the way people find what they love. As a Machine Learning Engineer, your focus will be on building, production-izing and scaling of machine learning models, and promoting engineering excellence. You will have the opportunity to work with data scientists and engineers, as well as lead work cross-functionally with Strategy, Product, Merchandising, Marketing, and Engineering partners to build and enhance those capabilities.
You're excited about this opportunity because you will…
Bring your engineering excellence to improve how we serve real time recommendations in production at scale.
Make a substantial impact on personalization across multiple dimensions by creating the infrastructure that allows us to build the next generation of recommendation systems
Collaborate with data scientists on a variety of sophisticated machine learning algorithms
Work closely with partners in ML Platform Eng, Engineering, Product and Merchandising teams
Be empowered to take initiative and follow your innate curiosity
We’re excited about you because…
You have experience building, deploying and maintaining high performing, resilient, and scalable real time machine learning systems
You are familiar with the fundamentals of ML in at least one of these areas: supervised learning, recommendation systems, or deep learning.
You are familiar with Python and modern ML frameworks such as PyTorch or TensorFlow.
You are a clear communicator who can get buy-in from partners and you are excited to be part of a team
You are curious, inspired to take on new challenges and calculated risks.
You’re happiest as a team player, able to balance time against multiple systems and work streams with defined objectives
Why you'll love working at Stitch Fix...
We are a group of bright, kind people who are motivated by challenge. We value integrity, innovation and trust. You’ll bring these characteristics to life in everything you do at Stitch Fix.
We cultivate a community of diverse perspectives— all voices are heard and valued.
We are an innovative company and leverage our strengths in fashion and tech to disrupt the future of retail.
We win as a team, commit to our work, and celebrate grit together because we value strong relationships.
We boldly create the future while keeping equity and sustainability at the center of all that we do.
We are the owners of our work and are energized by solving problems through a growth mindset lens. We think broadly and creatively through every situation to create meaningful impact.
We offer comprehensive compensation packages and inclusive health and wellness benefits.
Compensation and Benefits
This role will receive a competitive salary, benefits, and equity. The salary for US-based employees hired into this role will be aligned with the range below, which includes our three geographic areas. A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, location, and performance.This position is eligible for new hire and ongoing grants of restricted stock units depending on employee and company performance. In addition, the position is eligible for medical, dental, vision, and other benefits. Applicants should apply via our internal or external careers site.
Salary Range
$131,900 — $194,000 USD
This link (https://www.cigna.com/legal/compliance/machine-readable-files) leads to the machine readable files that are made available in response to the federal Transparency in Coverage Rule and includes negotiated service rates and out-of-network allowed amounts between health plans and healthcare providers. The machine-readable files are formatted to allow researchers, regulators, and application developers to more easily access and analyze data.
Please review Stitch Fix's US Applicant Privacy Policy and Notice at Collection here:https://stitchfix.com/careers/workforce-applicant-privacy-policy
Recruiting Fraud Alert:
To all candidates: your personal information and online safety are top of mind for us. At Stitch Fix, recruiters only direct candidates to apply through our official career pages athttps://www.stitchfix.com/careers/jobsorhttps://web.fountain.com/c/stitch-fix.
Recruiters will never request payments, ask for financial account information or sensitive information like social security numbers. If you are unsure if a message is from Stitch Fix, please emailcareers@stitchfix.com.
You can read more about Recruiting Scam Awareness on our FAQ page here:https://support.stitchfix.com/hc/en-us/articles/1500007169402-Recruiting-Scam-Awareness
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Machine Learning Engineer - Foundational Models
Machine Learning Engineer - Foundational Models at Stitch Fix (View all jobs) (https://www.stitchfix.com/careers/jobs) Remote, USA About Stitch Fix, Inc. Stitch Fix (NASDAQ: SFIX) is the leading online personal styling service that helps people discover the styles they will love that fit perfectly...
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