Machine Learning Engineer

Job Title : Machine Learning Engineer

Client : Optimum Data Analytics

Location : Remote (India)

Experience : 6- 8 Years

Employment Type : Full-time

Notice Period : Immediate to 15 Days

About Optimum Data Analytics :

Optimum Data Analytics is a trusted technology partner delivering turnkey AI solutions. We help organizations accelerate digital transformation by powering decision-making with advanced analytics and AI. With a team of statisticians, engineers, data scientists, and product managers, we bring clarity, agility, and innovation to businesses across industries. Our mission is to transform how AI/ML is applied in the service sector and deliver measurable outcomes that matter.

Role Overview :

We are seeking an experienced Machine Learning Engineer to join our advanced analytics and AI team. The ideal candidate will design, develop, and deploy ML models at scale, working with large datasets and leveraging modern ML frameworks. Hands-on experience with Large Language Models (LLMs) such as OpenAI or Hugging Face is highly desirable. This is an exciting opportunity to work on cutting-edge projects in a fast-paced environment.

Key Responsibilities :

- Design, build, and deploy scalable ML models for real-world applications.

- Develop and optimize end-to-end ML pipelines using PySpark and MLflow.

- Process structured and unstructured data with Pandas, NumPy, and other libraries.

- Train, evaluate, and fine-tune models using scikit-learn, TensorFlow, or PyTorch.

- Integrate and experiment with LLMs (e.g., OpenAI GPT, Hugging Face Transformers).

- Collaborate with data engineers, product managers, and software developers.

- Monitor and improve model performance for accuracy, scalability, and reliability.

- Ensure reproducibility and version control of ML experiments using MLflow.

Required Skills :

- Strong programming expertise in Python.

- Solid understanding of machine learning algorithms and model evaluation techniques.

- Experience with PySpark for big data processing.

- Proficiency with MLflow for model lifecycle management.

- Strong hands-on with Pandas, NumPy, Scikit-learn.

- Familiarity with LLMs (OpenAI, Hugging Face Transformers).

- Knowledge of MLOps principles and deployment best practices.

Preferred Qualifications :

- Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or related fields.

- Experience with cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI).

- Strong analytical, problem-solving, and communication skills.

- Collaborative mindset with ability to work in cross-functional teams.