Machine Learning Engineer

We are seeking a highly skilled Machine Learning Engineer to join our team. The ideal candidate will possess a strong background in Machine learning (ML), Deployments and Python programming. This role involves collaborating closely with data scientists, product managers, and data engineers to design, develop, and deploy high-performance AI/ML models.

Responsibilities:

- Collaborate with cross-functional teams to design and deliver high-performance AI models

- Deploy OR and ML solutions into the cloud.

- Train, tune, and optimize AI/OR models and algorithms for enhanced performance.

- Implement complex real-time data and AI/ML applications to capture knowledge and automate decision-making processes.

- Create ML/AI models for business teams and establish metrics to track their accuracy and performance.

- Oversee the full lifecycle of algorithm development, from ideation to deployment and monitoring.

- Evaluate and rank ML algorithms based on their potential success in solving specific problems.

- Serve as an internal resource for AI/ML needs, providing guidance and insights to stakeholders during strategic discussions.

Requirements:

- Minimum of 5-7 years of experience in ML engineering with large-scale production systems.

- Strong experience with Azure cloud computing and containerization technologies (like Docker, Kubernetes).

- Experience with Python/OOPs programming languages and data science frameworks like (Pandas, Numpy, TensorFlow, Keras, PyTorch, sklearn).

- Knowledge of DevOps tools such as Git, Jenkins, Sonar, Nexus is must.

- Building python wheels and debugging build process.

- Data pipeline building and debugging (by creating and following log traces).

- Basic knowledge of DevOps practices.

- Concepts of Unit Testing and Test-Driven development.

- SDE skills like OOP and Functional programming are an added advantage.

- Experience with Databricks and its ecosystem is an added advantage.

Machine Learning:

- Proficient in Machine Learning techniques both supervised and unsupervised

- Expertise in using ML/AI libraries such as Pandas, NumPy, PyTorch, TensorFlow and traditional ML algorithms (3+ years)

Deployments:

- Implementation of CI/CD pipeline using GitHub Actions or Jenkins

knowledge of external tools like SonarQube, Prisma scan.

- Python Programming and Software Engineering

- Expertise in Pythonic clean coding practices, including the use of decorators, generators, and descriptors (3+ years).

- Strong understanding of software design principles such as DRY, OAOO, YAGNI, KIS, EAFP/LBYL, and defensive programming (2+ years).

- Proficient in software design concepts focusing on cohesion and coupling (2+ years).

- Knowledge of SOLID principles (2+ years).

- Good understanding of OOPS concepts and LLDs

Education and Experience:

- Minimum Bachelor's degree or foreign equivalent in Computer Science, Electrical Engineering, or a closely related field.

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