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Day to Day

As a Staff Machine Learning Engineer in our Staffing Technology Marketplace group, you'll own the source data, the models and the business impact behind Indeed's AI-first staffing platform, which agencies, employers and the MSPs that coordinate them use every day to take orders, book workers and manage shifts. Through Indeed and our own Indeed Flex agency, we see labor-market activity at a scale no single agency can: workers looking for work, employers creating demand, shifts being worked. You'll set the technical direction for turning that into models that predict whether a booked worker will turn up, whether and how fully an order will fill, and which orders are at risk early enough for someone to act. You'll then turn those predictions into decisions customers act on and increasingly trust the platform to make for them: how many backups to book, which agencies an MSP should release an order to and in what sequence within contracted volume splits, and what pay rate will achieve the fill and quality a client asked for without overspending.

On a typical day you'll work with customers and our business, product and engineering teams to define, build and evaluate production models per market in the US and UK. You'll keep them healthy and catch a model degrading for a single customer before they notice. You'll design ranking and reliability scoring that balances today's fill against the long-term health of the worker pool, so the same few workers aren't overused while everyone else drifts away. You'll make models work from day one for a new agency with no history, and hold up on the thin data most agencies have. Every recommendation needs to be explainable to the person acting on it and configurable to each agency's risk appetite. You'll use what the models show to shape the roadmap with product, engineering and design, and work with legal and engineering partners on foundational questions, such as what can be learned across agencies and what must stay separate.

Responsibilities

+ Partner with cross-functional teams to enhance and optimize search algorithms for improved accuracy, relevance, and overall user experience.

+ Experiment with Proof of Concept Machine Learning model improvements, scale them to production, and run iterative A/B experiments to improve our matching technology while partnering with other teams

+ Define and clarify project priorities, deliverables, and success criteria in partnership with cross-functional teams.

+ Act as a bridge between technical and non-technical collaborators, facilitating effective communication and comprehension of project goals and outcomes.

+ Mentor and grow other software engineers and Machine Learning Engineers across teams

+ Break down larger Machine Learning initiatives into pieces that deliver incremental business value and guide the team through implementing them

+ Represent Indeed at major Machine Learning conferences, such as Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the International Conference on Learning Representations (ICLR).

Skills/Competencies

+ Requires a Bachelor's degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience

+ Proven experience building ML for two-sided marketplaces, staffing, on-demand labor or similar operational businesses, including experiment design where marketplace interference rules out clean A/B tests.

+ Proven experience solving cold-start and sparse-data problems in production, in multi-tenant B2B settings where each customer's data and configuration differ: models that work from day one for a new customer with no history and hold up on thin data, built on well-calibrated probabilistic predictions (classification, forecasting) under uncertainty.

+ Prior success in deploying impactful Machine Learning solutions to large-scale production systems, while partnering across teams

+ Solid knowledge of data structures and algorithms

+ Sense of ownership and accountability as a key contributor in the technical and product domains

+ Knowledge and practical experience working on Deep Learning Libraries (like Torch, Tensorflow, etc.)

+ Excellent written and verbal communication in English, effective with technical and business audiences

Salary Range Transparency

Tier 1 - United States of America 163,000 - 245,000 USD per year

Tier 2 - United States of America 182,000 - 272,000 USD per year

Tier 3 - United States of America 199,000 - 299,000 USD per year

Tier 4 - United States of America N/A

Tier 5 - United States of America 227,000 - 341,000 USD per year

Salary Range Disclaimer

The base salary range represents the low and high end of the Indeed salary range for this position in the given work location. Actual salaries will vary depending on factors including but not limited to location, and experience. The range(s) listed is just one component of Indeed's total compensation package for employees. Other rewards may include quarterly bonuses, Restricted Stock Units (RSUs), a Paid Time Off policy, and many region-specific benefits. Compensation may also vary based on where a role is performed, as work locations are grouped into geographic pay tiers to reflect cost of labor differences in different geographic markets. Candidates can view geographic pay tiers by location on our career site ( https://www.indeed.com/careers/paytiers ), and recruiters can confirm how location is considered for a specific role.

Benefits - Health, Work/Life Harmony, & Wellbeing

We care about what you care about. We have a multitude of benefits to support Indeedians, as well as their pets, kids, and partners including medical, dental, vision, disability and life insurance. Indeedians are able to enroll in our company's 401k plan, as well as an equity-based incentive program. Indeedians will also receive open paid time off, 11 paid holidays a year and up to 26 weeks of paid parental leave. For more information, select your country and learn more about our employee benefits, program, & perks at https://www.indeed.com/careers/benefits !

Equal Opportunities and Accommodations Statement

Indeed is deeply committed to building a workplace and global community where inclusion is not only valued, but prioritized. We're proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, fam...

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