This role is for one of the Weekday's clients

Salary range: Rs 2000000 - Rs 4500000 (ie INR 20-45 LPA)

Min Experience: 2 years

Location: Bengaluru

JobType: full-time

We’re seeking a talented and proactive Machine Learning Engineer to join our fast-growing team. In this role, you'll work on innovative ML projects that tackle real-world challenges across diverse domains. As a key member of our engineering team, you’ll collaborate closely with data scientists, software engineers, and product managers to design, build, and deploy scalable machine learning solutions that drive meaningful impact.

Requirements

Key Responsibilities:

• Design, develop, and deploy machine learning models across a range of business applications.
• Partner with product teams to translate user needs into effective ML-driven features and tools.
• Explore and implement novel algorithms to boost model accuracy and performance.
• Build and optimize data pipelines for processing and handling large-scale datasets efficiently.
• Continuously monitor and fine-tune models to maintain accuracy and relevance in production.
• Stay abreast of the latest research and advancements in machine learning and AI.
• Create internal tools and libraries to streamline the end-to-end ML development lifecycle.
• Document models, methodologies, and results for both technical and non-technical stakeholders.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.
• 2+ years of hands-on experience in machine learning or a related role.
• Strong grasp of ML algorithms, statistical modeling, and data structures.
• Proficiency in Python and experience with ML frameworks like TensorFlow, PyTorch, or similar.
• Proven experience deploying and managing models in production environments.
• Familiarity with cloud platforms (e.g., AWS, GCP, Azure) for ML workloads.
• Solid foundation in data preprocessing, feature engineering, and model evaluation techniques.
• Comfortable working with large datasets and contributing in collaborative, cross-functional teams.
• Problem-solving mindset with a passion for building scalable and efficient systems.

Nice to Have:

• Experience with deep learning, natural language processing (NLP), computer vision, or reinforcement learning.
• Familiarity with containerization tools like Docker and orchestration tools like Kubernetes.
• Understanding of MLOps practices including model versioning, CI/CD for ML, and monitoring.
• Strong communication skills and the ability to explain technical concepts to non-technical audiences.