Senior Machine Learning Engineer - Deep Learning Models
Talent SniffersBangalore28 days ago
Job descriptionEnd-to-End ML Application Development : Design, develop, deploy ML models / systems into production (robust, scalable, high-performing) Software Design & Architecture : Create clean, modular, testable ML pipelines, APIs, services; make architectural decisions ML Model Development & Optimization : Collaborate for business understanding, explore data, build / train / evaluate ML models learning), optimize models Data Engineering for ML : Build data pipelines for feature engineering, data handling / versioning MLOps & Productionization : Implement best practices (CICD, auto-testing, model versioning / monitoring, alerting for drift / bias) Performance & Scalability : Diagnose / fix bottlenecks, make models scalable / reliable Collaboration / Mentorship : Work with cross-functional teams (data scientists, SW engineers, PMs, DevOps), possibly mentor juniors Research / Innovation : Stay updated on ML / MLOps tech, suggest / explore improvements Documentation : Write clear docs for ML models, pipelines, services Education : Bachelors or Masters in CS, ML, Data Science, EE, or similar Experience : 5+ years professional ML / swe engineering (strong ML focus) Programming : Expert-level Python (clean, efficient code); other languages (Java, Go, C) a bonus Software Fundamentals : Patterns, structures, algorithms, OOP, distributed systems ML Expertise : Theory / practice with ML algorithms; frameworks (PyTorch, Scikit-learn); feature engineering; metrics; tuning Data Handling : SQL / NoSQL databases; handling big datasets Problem-Solving : Strong analytical / pragmatic approach Communication : Clear technical / non-technical explanation skills Masters / PhD in relevant field Big data (Spark, Hadoop, Kafka) experience Open-source / personal project portfolio AB testing, experimental design for ML Data governance, privacy, security knowledge in ML
Job Title : Senior Machine Learning Engineer Applied AI
The candidate should be :
- A strong software engineer with deep ML expertise
- A pragmatic data scientist
- Skilled in building robust, scalable ML applications
- Able to bridge ML research and production-ready systems
Key Responsibilities :
Required Qualifications :
Preferred Qualifications :
This role requires someone strong technically, and capable of owning ML products end-to-end while working across teams and mentoring junior engineers. The candidate needs both research and practical production experience in ML systems.
(ref : hirist.tech)
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Machine Learning Engineer Learning • Bangalore
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