India onlyThis role is for one of the Weekday's clients
Salary range: Rs 5000000 - Rs 10000000 (ie INR 50-100 LPA)
Min Experience: 1 years
Location: Remote (India)
JobType: full-time
We're looking for a Machine Learning Engineer to join our growing team and help shape the intelligence behind our platform. In this role, you’ll design, build, and deploy scalable ML models that solve meaningful business problems. You’ll work closely with data scientists, product managers, and engineers to transform raw data into real-world impact.
Whether you're early in your ML journey or bring years of experience, this role offers opportunities to work on end-to-end ML systems—from ideation to production.
Requirements
What You’ll Do
- Build, train, and deploy machine learning models to solve high-impact business challenges.
- Analyze large-scale datasets to uncover insights and improve model accuracy and performance.
- Collaborate with cross-functional teams to understand product goals and translate them into ML solutions.
- Develop and maintain production-grade ML pipelines and workflows.
- Monitor model performance in production and iterate based on real-time feedback and data drift.
- Stay updated with the latest research, tools, and trends in AI/ML and apply them to improve our systems.
What We’re Looking For
- 1–10 years of hands-on experience in ML, data science, or a similar field.
- Strong programming skills in Python and experience with ML libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
- Proficiency in data analysis and processing tools like Pandas, NumPy.
- Understanding of ML concepts, model evaluation techniques, and algorithms.
- Experience with cloud platforms (AWS, GCP, or Azure) for model deployment is a plus.
- Ability to write clean, maintainable, and scalable code for production environments.
- Strong problem-solving mindset, attention to detail, and ability to communicate complex ideas clearly.
Bonus Points For
- Experience with MLOps tools and practices.
- Exposure to deep learning, NLP, or recommendation systems.
- Experience working in agile, fast-paced environments.
