Senior / Staff Machine Learning Engineer position at Shiftsmart.| United States Of America

Shiftsmart Senior / Staff Machine Learning Engineer

Experience: General

Pattern: full-time

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Bachelor's (B.Sc.)

New York City ..........United States Of America

Why Shiftsmart We’re building the Amazon of labor. We’re a labor platform pairing end-to-end workforce management technology with a rapidly growing global network of 5M flexible workers to create scalable labor solutions for the largest companies in the world, like Circle K, Pepsi, Dollar General, Starbucks and more. Our unique business model fractionalizes jobs down to shifts and makes it easy for workers to work across multiple companies through a digital marketplace. We’re one of the fastest-growing startups in the country. We’ve grown 2-3x each year since we started and raised $120M+ from top-tier investors including D1 Capital & Imaginary Ventures …and we’re only getting started. Our mission is to build the world’s leading platform for hourly workers and enterprises enabling flexibility, choice, and upward social mobility. Join a rocketship. This is a unique opportunity to join the ground floor of a rapidly scaling business that is changing the way hourly labor works and capturing a $2 trillion dollar opportunity in the US alone. Ownership + impact. Join a team that is challenging and supporting one another to build a great business and create flexibility, choice, and upward social mobility for workers everywhere. Captain your career path. Enjoy accelerated learning and growth working with a world-class team from top tech companies (e.g. Uber, Airbnb, Google, Amazon), business schools (e.g. HBS, GSB, Wharton), and professional services (e.g. Bain, BCG, Goldman). Become a world-class executor. We believe that #ExecutionIsBinary, and are dedicated to helping you master that skill for life here and beyond. Mission: Why this role exists The Engineering Team enables Shiftsmart to anticipate and creatively solve problems across multiple functions with solutions that have a lasting impact for both our customers (employers) and our users (workers). Our mission is simple: To build the world’s leading platform for hourly workers and enterprises enabling flexibility, choice, and upward social mobility. Our Machine Learning Engineers will define how machine learning is applied to the vast amounts of data collected from our labor marketplace to generate business value for Shiftsmart. They will build and ship end-to-end ML systems amidst ambiguity and use our marketplace data to solve problems such as matching and dispatching relevant shifts to workers, identifying the best partner to fulfill a shift, and predicting our likelihood to fill shifts network wide. Shiftsmart is based in New York City with typically 4 days in office. Outcomes: The problems you will solve Architect, design and build highly-performant and reliable ML systems from the ground up, which integrate into our production environment (Python, MongoDB, GCP services). Iteratively develop, train, and deploy high-scale, high-performance ML models that can, for example, efficiently price work (shifts), and maximize fill rates by modeling the likelihood of shift acceptance. Work on developing new computer vision models that will allow our team to assess inventory and building models that allow our time to access real time fill rates for shelves and coolers Contribute to our engineering culture and serve as a mentor for junior engineers. Competencies: Who you are Machine learning expert: 5+ years of machine learning and software engineering experience, including the end-to-end, ground-up ML projects typically found in early-stage start-ups. Large dataset wrangler: Track record of working with very large datasets to solve business problems by iteratively training and deploying highly performant machine learning models into production. Programming expert: Hands-on programming skills in Python (or similar languages), data manipulation (SQL, pandas), and machine learning tools (scikit-learn, XGBoost, etc.) Business acumen: You can understand the Shiftsmart business from multiple perspectives using your business savvy, customer focus, financial acumen, and technical savvy. Results-driven: You are driven for results, taking the initiative to plan and execute projects from scratch in rapidly evolving environments, with significant complexity and ambiguity. Collaborative: You can build collaborative relationships and influence the overall product roadmap using your communication skills to effectively partner with leadership and cross-functional teams Computer Vision Expert: Experience with classification, action recognition, object detection, and person tracking/reidentification tasks in images and video, and their application to solve real world problems Compensation philosophy To provide greater transparency we share base salary ranges, which are based on role and level benchmarked against similar stage, high growth companies. Offers are determined based on multiple factors including skills, work experience, and relevant credentials. In addition to competitive salaries and meaningful equity we offer the following benefits: Comprehensive healthcare coverage: We cover 100% of employee premiums for medical, dental, and vision care (60-75% for dependents) 401(k) match program: We match 100% on the first 3% of your contributions and 50% on the next 2% for a maximum match of 4% Generous, fully paid parental and family leave policies Pre-tax commuter benefits Collaborative office with fully stocked kitchen @ 1 World Trade in Manhattan Equal opportunity employer Shiftsmart is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Operating Principles @ Shiftsmart Inspired by Leadership Principles @ Amazon Execution Is Binary We #GetShiftDone. We take immense pride in both the quality of our work and our relentless determination to deliver on our commitments. If we say we are going to do something, we do it. We own the outcome with an unstoppable mindset through the finish line and are impatient to move the ball forward. This means we work really hard, execute with urgency, and ruthlessly challenge timelines for anything important. As a result, we do not defer responsibility to other teams or individuals. Instead, we take the problem as far as we can and only when needed ask others for help. Each time a crisis or opportunity emerges we take the hill as one team, because we are allergic to the words “it can’t be done” . Missionaries, Not Mercenaries We before me. We believe in our mission to build a better world for workers. We understand why our work matters and take seriously how it impacts our customers and our partners. This belief permeates everything we do from the strategic to the mundane. We are energetic, ambitious, and want to win. We constantly raise the standards for ourselves and everyone around us. We show up for our customers, our partners, and most importantly our teammates, and make every effort to build lasting relationships with each of them. We do not measure success based on our titles or the size of our empires. This also means we put the needs of the business before the details of our job descriptions. Rather than fight for a bigger piece of the pie, we fight to grow the entire thing and recognize this is how to grow our careers too. Inputs > Outcomes We work really hard. Fundamentally changing how labor works is not easy. It often requires long days, late nights, and weekends to deliver on our commitments. We lean into this challenge. We focus on the process. We think in terms of value chains and appreciate that a bad process with a good outcome is simply dumb luck. We lead with data. We use facts, not fiction, to build narratives and make decisions. To do this we prepare written memos in advance and resist the urge to engage in endless water cooler what ifs, because we value the time and attention of our teammates. We hire and develop the best. When we decide to hire a new team member, we do so because we believe they will increase the talent density on our team. We view ourselves as leverage maximizers rather than inconvenience reducers and strive to increase the output of everyone we interact with. Honesty Over Harmony We share the truth even when it is painful. We do not, however, share the truth callously to hurt people’s feelings or make them look bad. We also assume positive intent. If someone is not delivering in a way that we need, we ask them and tell them before assuming the worst. We embrace mutual feedback. As people leaders we care more about our team’s growth and success than how much others like us. As individuals we seek, accept, and apply feedback. We do not give or take feedback personally because we understand it enables us to learn and grow. We tell the truth to ourselves. We reject a pollyannaish view of our world. Instead if something isn’t going well that we are responsible for, we call it out. And when someone calls out their own truth that may be less optimal, we don’t punish them for it. We have the meeting in the meeting. If something is broken or we disagree, we call it out and say something in the moment even if it feels uncomfortable to do so. This means that if something is broken, we do not just accept it and complain later. Invent & Iterate We are inventors @ heart. We categorically reject the phrase “that is how it’s always been done” , and constantly discover new and better ways to do more with less. This means we are resourceful and often do things that don’t scale, only to create ways to scale them later. We’re builders. We think BIG. At every level of the company, we embrace big, hairy, audacious, and transformative goals. We fear lack of progress and incremental thinking more than failing to deliver or falling short of an audacious goal. We believe courage means to try without fear and learn without ego. We do not let perfect get in the way of better. When faced with the choice we prioritize delivering something, even if imperfect, over endless debate and alignment. We embrace good mistakes.

Senior / Staff Machine Learning Engineer job opportunity at Shiftsmart.

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