Anlage Infotech
Senior Machine Learning Engineer
Skills
2 months ago
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Important information
Contract type:
Permanent
Salary:
₹3,000,000 – ₹4,500,000 / year
Location:
Bengaluru, Karnataka, India
Work mode:
Hybrid
Published on:
18 August 2026
What they need
Senior Machine Learning Engineer
Experience: 10+ Years
Location: Bangalore
Employment Type: Full-Time
Work Mode: [Hybrid]
Job Summary
We are looking for an experienced Senior Machine Learning Engineer with 10+ years of professional experience in Machine Learning Engineering, Software Engineering with a strong ML focus, or a similar role.
The ideal candidate will combine strong software engineering fundamentals with deep expertise in machine learning, data processing, model development, and production-grade ML solutions. The role requires hands-on experience with Python, PyTorch, Scikit-learn, ML algorithms, feature engineering, model evaluation, hyperparameter tuning, SQL/NoSQL databases, and large-scale data processing.
The successful candidate should be able to translate complex business and technical problems into practical, scalable ML solutions and communicate effectively with both technical and non-technical stakeholders.
Key Responsibilities
Machine Learning Engineering
- Design, develop, implement, and maintain machine learning models and solutions for complex business problems.
- Apply strong theoretical and practical knowledge of machine learning algorithms to real-world use cases.
- Select appropriate algorithms, approaches, and techniques based on business and technical requirements.
- Perform feature engineering, model training, validation, evaluation, and optimization.
- Define and analyze appropriate model evaluation metrics.
- Perform hyperparameter tuning and model optimization.
- Collaborate with engineering and data teams to transition ML models into production-ready solutions.
Software Engineering
Develop clean, efficient, scalable, production-grade, and well-documented Python code.
Apply strong software engineering principles to ML systems and applications.
Design reusable and maintainable software components using appropriate design patterns and object-oriented programming principles.
Apply strong knowledge of:
Data Structures
Algorithms
Object-Oriented Programming
Software Design Patterns
Distributed Systems
Ensure solutions are scalable, reliable, maintainable, and efficient.
Data Engineering & Data Handling
- Work with large and complex datasets to support machine learning initiatives.
- Develop data processing and transformation workflows required for ML model development.
- Work with both SQL and NoSQL databases.
- Apply knowledge of data warehousing concepts and large-scale data processing.
- Perform data analysis, preparation, validation, and feature extraction.
- Collaborate with data engineering teams to ensure availability and quality of data required for ML applications.
ML Frameworks
Develop machine learning solutions using frameworks and libraries including:
PyTorch
Scikit-learn
Evaluate and select appropriate frameworks and techniques based on the requirements of the solution.
Maintain and optimize ML implementations for performance and scalability.
Problem Solving & Innovation
- Analyze complex technical and business problems and develop pragmatic, scalable solutions.
- Evaluate different approaches and make data-driven technical decisions.
- Identify opportunities to improve existing ML models, processes, and engineering practices.
- Troubleshoot model, data, and application-related issues.
- Balance technical excellence with practical business requirements and delivery timelines.
Collaboration & Communication
- Work closely with Data Scientists, ML Engineers, Software Engineers, Data Engineers, Product Managers, and other stakeholders.
- Translate business requirements into technical and ML solutions.
- Explain complex machine learning and technical concepts clearly to technical and non-technical audiences.
- Prepare technical documentation and communicate solution approaches, assumptions, limitations, and outcomes.
- Collaborate effectively across teams to deliver high-quality solutions.
Required Qualifications
Education
Masters degree in:
Computer Science
Machine Learning
Data Science
Electrical Engineering
or another related quantitative field.
Experience
10+ years of professional experience in:
Machine Learning Engineering
Software Engineering with a strong ML focus
or a closely related role.
Programming
Must Have:
Strong proficiency in Python.
Experience writing:
Production-grade code
Clean and maintainable code
Efficient code
Well-documented code
Good to Have:
Experience with additional programming languages such as:
Java
Go
C++
Software Engineering Fundamentals
Strong understanding of:
- Software Design Patterns
- Data Structures
- Algorithms
- Object-Oriented Programming
- Distributed Systems
- Software Development Best Practices
Machine Learning
Strong theoretical and practical knowledge of:
- Machine Learning Algorithms
- Supervised Learning
- Unsupervised Learning
- Feature Engineering
- Model Evaluation
- Evaluation Metrics
- Hyperparameter Tuning
- Model Optimization
ML Frameworks
- PyTorch
- Scikit-learn
Data
- Strong experience with SQL.
- Experience with NoSQL databases.
- Understanding of data warehousing concepts.
- Experience processing and working with large datasets.
Good-to-Have Skills
- Java
- Go
- C++
- Experience with distributed ML systems.
- Experience taking ML models from development through production.
- Exposure to ML pipelines and production ML environments.
- Experience with cloud-based ML platforms.
- Knowledge of MLOps practices.
Key Competencies
- Strong analytical and problem-solving skills.
- Pragmatic approach to solving complex problems.
- Strong software engineering mindset.
- Ability to work independently as well as collaboratively.
- Strong verbal and written communication.
- Ability to explain complex technical concepts to diverse audiences.
- Strong ownership and execution capabilities.
- Ability to work effectively in a fast-paced technical environment.
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