Machine Learning Engineer - Recommendation Systems
full-time•Bengaluru
About this role
Job Title
Collaboration
Machine Learning Engineer – Recommendation Systems
LocationBangalore
Experience3–8 years (flexible based on depth in ML systems)
Job DescriptionWe are looking for a Machine Learning Engineer (Recommendations) to design, build, and scale personalized recommendation systems that power discovery, ranking, and user engagement across our products. You will work at the intersection of machine learning, data engineering, and backend systems, taking models from research to production.
Key ResponsibilitiesRecommendation & ML- Design and develop recommendation systems including:
- Collaborative Filtering (user-item, item-item)
- Content-based and hybrid recommenders
- Ranking and re-ranking models
- Embedding-based retrieval (ANN, vector search)
- Train, evaluate, and iterate on models using offline metrics (NDCG, MAP, Recall@K) and online A/B experiments
- Build pipelines for feature engineering, model training, inference, and retraining
- Deploy ML models in production environments with low-latency constraints
- Optimize inference for scale (caching, batching, approximate nearest neighbors)
- Build real-time and batch recommendation pipelines
- Monitor model performance, data drift, and system health
- Work with large-scale datasets (clicks, impressions, transactions)
- Define success metrics for recommendations (CTR, CVR, retention)
- Run and analyze A/B tests and iterate based on results.
Collaboration
- Work closely with product, data, and backend teams to translate business problems into ML solutions
- Contribute to ML best practices, documentation, and system design
- Strong understanding of:
- Recommendation algorithms
- Ranking and learning-to-rank
- Embeddings and similarity search
- Experience with Python and ML libraries (PyTorch / TensorFlow / Scikit-learn)
- Strong SQL skills; experience with large datasets
- Experience with feature stores, data pipelines, and batch/stream processing
- Familiarity with vector databases / ANN libraries (FAISS, ScaNN, Elasticsearch/OpenSearch KNN, Milvus)
- Experience deploying models using REST/gRPC services
- Familiarity with Docker, Kubernetes, or cloud platforms (AWS / GCP / Azure)
- Understanding of latency, throughput, and scalability trade-offs
- Experience with:
- Search or feed ranking systems
- Hybrid retrieval (BM25 + embeddings)
- Real-time recommendations
- Knowledge of:
- Kafka / streaming systems
- MLOps tools (MLflow, Airflow)
- Experience in e-commerce, ads, content platforms or marketplaces
- Personalized home feeds and search ranking
- “People also viewed” recommendations
- Cold-start and long-tail problems
- Large-scale experimentation and model optimization
- Strong problem-solving and system-thinking mindset
- Ability to balance model quality vs production constraints
- Comfortable owning models end-to-end
What you'll do
- Design and develop personalized recommendation systems while deploying ML models in production environments. Monitor model performance and collaborate with cross-functional teams to translate business problems into ML solutions.
About Apna
Founded in 2019, Apna Group is redefining the future of work for India and beyond - empowering millions of professionals and enterprises through AI-led innovation.
Through Apna.co, India’s largest early-career job marketplace, we’ve connected 6 Cr+ job seekers with 7 Lakh+ employers across 900+ cities, enabling faster, smarter, and more meaningful hiring at scale.
Trusted by India’s leading enterprises such as Teleperformance, Zomato, HDB Financial Services, Bluestar, TVS, Kotak, Axis Bank, Flipkart, and Lifestyle, Apna powers workforce transformation across Retail, BFSI, Staffing, Healthcare, Manufacturing, and IT sectors.
Building on this foundation, Apna has expanded into enterprise AI innovation with Blue Machines, our Voice AI platform that enables organizations to deploy production-grade voice agents with sub-300 ms latency and <1-week deployment cycles. In its first 45 days, Blue Machines secured $6 M+ in enterprise contracts across lending, insurance, recruitment, and healthcare - making it one of India’s fastest-adopted deep-tech platforms.
Explore more at bluemachines.ai
Recognized among India’s Most Preferred Workplaces 2025–26, and as a Most Preferred Workplace for Women, Apna Group continues to build technology that empowers people, strengthens enterprises, and drives inclusive growth.
Backed by world-class investors including Tiger Global, Sequoia Capital, Lightspeed, Insight Partners, GSV Ventures, and Owl Ventures, Apna collaborates with leading government and public institutions such as the NSDC, Ministry of Defence, UNICEF YuWaah, and AICTE to drive nationwide skilling and employability programs - powering AICTE’s career portal for over 3 million students across 22,000 colleges.
Visit: apna.co
For employer solutions, visit: employer.apna.co
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Frequently Asked Questions
What does a Machine Learning Engineer - Recommendation Systems do at Apna?
As a Machine Learning Engineer - Recommendation Systems at Apna, you will: design and develop personalized recommendation systems while deploying ML models in production environments. Monitor model performance and collaborate with cross-functional teams to translate business problems into ML solutions..
Is the Machine Learning Engineer - Recommendation Systems position at Apna remote?
The Machine Learning Engineer - Recommendation Systems position at Apna is based in Bengaluru, India. Contact the company through Clera for specific work arrangement details.
How do I apply for the Machine Learning Engineer - Recommendation Systems position at Apna?
You can apply for the Machine Learning Engineer - Recommendation Systems position at Apnadirectly through Clera. Click the "Apply Now" button above to start your application. Clera's AI-powered platform will help match your profile with this opportunity and guide you through the application process.