Machine Learning Engineer

Job Description

Machine Learning Engineer

Employment Type: Full time

Work Mode: Onsite (5 days)

Job Location: Whitefield, Bangalore

Welcome to WhiteBlue!

What Are We 

We are an exclusive cloud services company, transforming the world with digital technology. We excel in serving the customers with the right experienced, certified professional cloud talent. We are passionate about creating world class human capital which has Hands-on Cloud experience to build, migrate and support complex Cloud environments. We are keen in providing tailored services and solutions for each customer. We measure our success based on the business outcomes we deliver.

Who are We 

We are a bunch of passionate software professionals who love to work together and grow together!! We work, create, and inspire each other every day. We are a purpose driven collaborative team. We always want to give our best and we are dedicated towards achieving mutual success. Our corporate culture is unique, and each. employee is valued here. We are always ready to walk the extra mile to satisfy our customers. Leveraging our cutting-edge expertise, we provide the best solutions to the clients. We are outcome obsessed and customer centric. We love to walk the talk. At WhiteBlue, we create the future for our customers in the areas of Cloud, Data and IoT.

What are we looking for:

We are seeking a highly skilled Machine Learning Engineer who possesses expertise in developing and deploying machine learning models. The ideal candidate will have extensive knowledge and hands-on experience in utilizing Google Cloud Platform (GCP) services, particularly Vertex AI and AutoML Tabular, to create efficient and scalable ML solutions.

We need candidates who have more than 3 years of relevant experience.

Responsibilities:

1. Developing ML Models: Design, implement, and optimize machine learning models to solve complex business problems using advanced algorithms and techniques.

2. Utilizing GCP Services: Leverage Google Cloud Platform services such as Vertex AI and AutoML Tabular to streamline the model development, training, and deployment processes.

3. Data Preprocessing: Conduct data preprocessing, feature engineering, and data analysis to ensure the quality and relevance of input data for model training.

4. Model Evaluation and Optimization: Evaluate model performance, fine-tune hyperparameters, and optimize models for accuracy, scalability, and efficiency.

5. Integration and Deployment: Collaborate with software engineers to integrate machine learning models into production environments, ensuring seamless deployment and monitoring.

6. Documentation and Reporting: Document the entire ML pipeline, including methodologies, experiments, and outcomes. Generate reports and communicate findings to stakeholders.

Requirements:

- Effective communication skills and the ability to work collaboratively in a team environment.

- Bachelor's/masters degree in computer science, Engineering, or a related field. Holding an experience of 4 years at least in this tech stack and domain.

- Proven experience as a Machine Learning Engineer or Data Scientist with a focus on ML model development and deployment.

- Proficiency in programming languages such as Python, and familiarity with libraries like TensorFlow, Keras, or PyTorch.

- Hands-on experience with Google Cloud Platform services, specifically Vertex AI and AutoML Tabular, for model development and deployment.

- Strong understanding of ML concepts, algorithms, and techniques for supervised and unsupervised learning.

- Excellent problem-solving skills, analytical thinking, and attention to detail.

Preferred Qualifications:

- Experience in building end-to-end ML pipelines from data collection to model deployment.

- Familiarity with other GCP services, such as Big Query, Dataflow, and AI Platform, is a plus.

- Knowledge of advanced ML techniques like reinforcement learning, transfer learning, or NLP.

- Certifications in Google Cloud Platform or Machine Learning are advantageous.

- Any certification in ML and/or AI would be an added advantage,