Senior Machine Learning Engineer - Time Series & Computer Vision

About Us

Stylumia believes in augmenting human intelligence in fashion and lifestyle retail for a better world. With relevant data and the right technology, people and businesses in fashion and lifestyle retail can solve challenging problems and improve the world. In 2015-16, when we looked at the available technology and solutions, we saw that fashion forecasting and demand planning are subjective. We saw these methods do not solve the fundamental challenge in fashion trend spotting, and trend forecasting, and the business metrics of full-price sell-through continue to remain around the 50% mark creating over USD 750 billion/annum of wastage globally. The fashion industry's biggest wastage is caused by ill-informed decision-making.

We saw a need for a different kind of technology and approach, and we knew it would need a different type of company to build it. We formed Stylumia, a Deep Tech company solving fundamental retail challenges. Stylumia.ai is a global innovation-first Retail AI organization. We have products that impact the daily lives of varying multi-disciplinary personas across the value chain as we strive to help them eliminate wastage in the industry, by augmenting their decisions with consumer-backed insights.

Qualifications/Requirements

• Ability to self-start & work in a challenging environment by navigating ambiguity & by bringing structure. Work to solve problems vertically i.e. bringing in 0 to 1 progress.
• First Principle Problem Solving
• Around 2-4 years of experience working in a role within a quantitative field (e.g. Data Science, Applied Maths, Time Series Forecasting & Operations Research, Statistics, Computer Science, AI, Economics, or Engineering)
• Expertise in Python with strong coding skills, especially in data science libraries & frameworks such as pandas, numpy, scikit-learn, Tensorflow/PyTorch, pyspark, and experience with modern ML frameworks like Hugging Face Transformers.
• Strong expertise in data wrangling & analyzing massive complex datasets, structured & unstructured.
• Proven track record of extracting data insights & building ML models, especially in the areas of Predictive analytics, time series forecasting (Statistical models + Global models + LLM-based), and operations research through projects or internships taken earlier. Share links projects/Github repos
• Ability to work with cross-functional teams with high levels of collaboration
• Fundamental knowledge of Explainable AI and decoding Blackbox models.
• Proficiency in data visualization is a good to have - We look for candidates who are good at Storytelling.
• Strong written, verbal & interpersonal communication skills. Ability to communicate at all levels in the organization - Share blogs , articles that you have worked on which showcases your writing skills. Writing Is Thinking
• Strong problem-solving & project management skills & ability to handle multiple projects simultaneously & challenge the status quo in the organization if required.

Responsibilities

• Contribute to all the stages of data science projects: from translating a complex business problem into a data science problem to performing data analysis & modeling, and providing solutions to the business.
• Work closely with the forecasting team on fast-moving projects involving research and development within demand forecasting, allocation optimization, inventory planning, and other Retail use cases.
• Collaborate closely with leadership, engineering, and other stakeholders including product managers, and business and customer success teams to deliver impactful business insights.
• Work & Operate with a higher level of integrity (Do What We Say) & ability to expect the same in return from your co-workers.
• Engage in both research and engineering tasks, as we believe the boundary between these areas has dissolved with the advent of large models. Be prepared to conduct research and implement engineering solutions as needed.

Compensation & Employee Benefits

• Competitive Pay*
• Wealth Generation - Employee Stock Options (ESOPs) to own a stake in our success.
• No leave policy - We believe in trust and empowerment, allowing you to take the necessary time without any restrictive leave policy. Say goodbye to stressful leave approvals and hello to work-life harmony.
• Hybrid work setup
• Health Insurance with $O payroll deduction - Your well-being is our priority, and we've got you covered without financial strain!

Note: At Stylumia, engineers engage in substantial research, and researchers contribute significantly to engineering efforts. We value candidates who can bridge the gap between cutting-edge AI research and practical implementation in production environments.