Position Summary:

We are seeking a skilled Machine Learning Engineer to design, develop, and deploy ML models for various applications, including recommendation systems. The ideal candidate will implement and optimize machine learning algorithms to enhance model performance and accuracy while ensuring that enterprise infrastructure and data pipelines are equipped to support scalable ML solutions.

This role involves collaborating with ML engineers and stakeholders to translate business requirements into effective ML solutions. Responsibilities include designing scalable machine learning pipelines for data preprocessing, model training, and deployment, as well as enhancing model monitoring to track scalability and error rates. Additionally, the role focuses on ML model load testing, developing end-to-end test cases, and evaluating model scalability and latency under varying workloads. The candidate will automate test cases to ensure seamless model deployment and operation in production environments.

Responsibilities:

1. Design and develop machine learning models for various applications, such as recommendation systems.
2. Deploy machine learning solutions to meet enterprise goals and support experimentation and innovation.
3. Ensure that enterprise infrastructure and data pipelines are well-equipped to support machine learning solutions.
4. Implement and optimize machine learning algorithms to improve model performance and accuracy.
5. Collaborate with ML engineers, and stakeholders to understand business requirements and translate them into effective ML solutions.
6. Design and implement scalable machine learning pipelines for data preprocessing, model training, and deployment.
7. Enhance Monitoring of model scalability, and incident of increased error rate and ensure optimal results.
8. Focus on ML model load testing and creation of E2E Test Cases.
9. Evaluate models’ scalability and latency by running suites of metrics under different RPS and creating and automating the test cases for individual models, ensuring a smooth rollout of the models.

Qualifications:

1. Bachelor's or master's degree in computer science, Engineering, Mathematics, or a related field.
2. Minimum of 3-8 years of experience in machine learning, with a proven track record of building, monitoring, large scale ML models.
3. Strong problem-solving skills and understanding of recommendation system.
4. Strong programming skills in languages like Python, Scala, and Java.
5. Hands on experience in Databricks, mlFlow, Seldon, Kubeflow, Jenkins, Tecton.
6. Familiarity with custom machine learning platforms, feature store and monitoring ML Models.
7. Expertise in recommendation algorithms.
8. Experience with software engineering principals and use of cloud services like AWS.
9. Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams.

Mandatory Skills: Databricks, ML flow, Seldon, Kubeflow, ML Load Testing, AWS Services, Tecton, Jenkins, Java/Python/Scala, Evaluate Scalability & latency of Models.