We are looking for an experienced Machine Learning Engineer to join our team. The ideal candidate will have a strong foundation in algorithm design, complexity analysis, and hands-on experience in developing machine learning models from scratch. The role will involve building scalable and efficient ML systems, optimizing models, and integrating them into products. This individual should also be passionate about staying updated with new technologies and trends in the ML and AI space.

Key Responsibilities:

Be sharp at Algorithm Design and Complexity Analysis, solving new problems with ease with effective and computationally efficient methods

Enjoy programming and be comfortable with Object Oriented Programming in Python
Eager to quickly learn new concepts, languages, tools and technologies as required
Enjoy building products that are generic and can cater to multiple tenants, through appropriate parameterization/abstraction
Be excited to work in a startup environment and take end-to-end responsibilities working with the co-team members
Write clean, maintainable, and well-tested code
Engage in the full development life-cycle including architectural design and testing
Solid understanding of distributed systems Microservices/Reactive architecture, event driven systems, NoS L databases, queues, caching, docker containers, etc.

Required Skills:

Machine Learning and Algorithms:
- Strong experience in designing, implementing, and optimizing machine learning algorithms.
- Deep understanding of algorithms like Gradient Boosting, Random Forests, SVM, and clustering techniques.

2. Programming and Frameworks:

Proficiency in Python with a focus on ML frameworks such as TensorFlow, Keras, PyTorch, and Scikit-learn.
Familiarity with distributed computing and parallel processing for large-scale machine learning tasks.

3. Deep Learning and Advanced Models:

Understanding of deep learning architectures (e.g., CNNs, RNNs, GANs, etc.) and ability to implement them for real-world applications.

4. Data Processing and Tools:

Experience in working with large datasets and tools for data preprocessing, feature engineering, and model training.
Familiarity with big data tools like Spark and distributed ML libraries such as Spark-MLlib.

5. Cloud Technologies:

Experience with cloud platforms such as AWS, Azure, or Google Cloud for managing ML workloads and deployments.

6. Version Control and CI/CD:

Strong familiarity with Git-based version control and CI/CD practices for continuous integration of models.

7. Soft Skills:

Excellent problem-solving skills and ability to analyze complex datasets to extract valuable insights.
Strong communication and collaboration skills to work with cross-functional teams.

ualifications:

Education: Bachelor s degree in Computer Science, Engineering, Mathematics, or a related field.
Certifications: ML/AI-related certifications, such as from AWS, Google Cloud, or Azure, will be a plus.

Preferred ualifications:

Experience with machine learning libraries like TensorFlow, Keras, PyTorch, and Spark- MLlib.
Familiarity with cloud services (AWS, GCP, Azure) for deploying ML models at scale.
Experience in implementing end-to-end machine learning pipelines.

Senior Machine Learning Engineer

Job Description

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