Experience: 3.00 + years
Salary: Confidential (based on experience)
Expected Notice Period: 15 Days
Shift: (GMT+05:30) Asia/Kolkata (IST)
Opportunity Type: Office ()
Placement Type: Full Time Permanent position(Payroll and Compliance to be managed by: An AI-powered gaming commerce platform)
(*Note: This is a requirement for one of Uplers client - An AI-powered gaming commerce platform)
What do you need for this opportunity
Must have skills required:
Gaming, Gorse or LightFM, mobile, or consumer-engagement, Startup Experience, Python, PyTorch, FAISS, Scann, Gorse, Recommondation System, Recommender System
An AI-powered gaming commerce platform is Looking for:
Applied ML Engineer
About The Company
PS is India's first Gaming Commerce company, pioneering a new way for 500M+ gamers — to shop inside games.
PS is rebuilding how mobile games monetize. We sit between studios and brands, turning in-game engagement into real-world rewards for players — better LTVs for studios, higher retention for players, measurable performance for brands.
Unlike traditional ads, PS embeds commerce into gameplay itself, improving recall, conversion, and loyalty.
In under two years, PS has onboarded 20+ studios, 3,000+ brands, and reached 6M+ DAUs through its partners, backed by $1.6M funding from Jungle Ventures (Chimera), Audacity VC, IAN Capital Fund, 100x.VC, and leaders from Meta, Tata, Dyson, and Amazon.
The Role
We are looking for an
Applied ML Engineer with strong experience in
recommender systems to build the brain of PS's in-game commerce store — a recommendation engine that decides which products, coupons, and rewards to surface to which player, at which moment.
This role is ideal for someone who has worked on:
- Collaborative filtering and embedding-based retrieval in production
- Recommendation systems for marketplaces, deals, or content feeds
- Cold-start and sparse-data problems
- Bridging offline model development to online serving
Rigorous evaluation and a bias for shipping are
non-negotiable.
What You'll Do
- Own the collaborative filtering model (starting with Gorse, potentially moving to a custom stack)
- Build product embeddings (product2vec + Faiss / ANN) for the PS catalogue
- Evolve cohort assignment from rules-based to ML-driven
- Build the offline evaluation framework — precision@k, NDCG, conversion-rate, diversity, coverage
- Bridge offline models to online serving (model serving infrastructure, weekly refresh pipeline)
- Calibrate ranking weights against business outcomes (CTR, GMV, margin, repeat redemption)
- Partner closely with the Data Engineer (event pipeline + feature store) and Backend Engineer (ranking API, Redis serving layer)
- Translate sparse, noisy in-game event data into reliable signal
- Act as the internal owner of recommendation quality — always pushing on whether the model is actually lifting outcomes vs. just looking good on offline metrics
What We're Looking For
- 3–5 years of ML engineering experience, with recommender systems specifically
- Strong Python: PyTorch / JAX, scikit-learn, NumPy
- Hands-on with collaborative filtering — sparse matrices, cold start, production evaluation
- Embedding-based retrieval experience (Faiss, ScaNN, or equivalent)
- Proper reco evaluation chops — beyond accuracy: diversity, coverage, business-outcome metrics
- Comfort with sparse and noisy data
- Experience taking models from offline notebooks to online serving in production
- Clear communication and structured problem-solving
Strong Plus (Nice to Have)
- Experience building voucher, coupon, or deal recommendation systems
- Gaming, mobile, or consumer-engagement product experience
- Familiarity with Gorse or LightFM
- Experience with contextual bandits or online learning
- Feature store patterns
- Startup experience or ownership in fast-moving environments
How to apply for this opportunity
- Step 1: Click On Apply! And Register or Login on our portal.
- Step 2: Complete the Screening Form & Upload updated Resume
- Step 3: Increase your chances to get shortlisted & meet the client for the Interview!
About Uplers:
Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement.
(Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well).
So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!
