Job Description:

About the Role

We are seeking a talented Machine Learning Engineer to design, build, and deploy AI/ML models that power our products and solutions.
You will work closely with Data Scientists, Software Engineers, and Product teams to turn data into actionable insights and intelligent features.

This role is ideal for someone passionate about AI, predictive modeling, and scalable machine learning systems.

Responsibilities:

Key Responsibilities

• Design, develop, and implement machine learning models for production systems.

• Preprocess, clean, and analyze large datasets to extract features and insights.

• Build scalable ML pipelines using best practices in software engineering.

• Deploy models into production environments with monitoring and performance tracking.

• Collaborate with cross-functional teams (Data Science, Engineering, Product) to integrate ML solutions into products.

• Research and implement state-of-the-art ML algorithms and tools.

• Optimize model performance for speed, accuracy, and scalability.

• Stay up-to-date with the latest developments in AI/ML and recommend improvements.

• Document models, data workflows, and engineering processes.

• Participate in code reviews, testing, and quality assurance of ML solutions.

Preferred Qualifications:

Required Skills

• Strong knowledge of machine learning algorithms: regression, classification, clustering, recommendation systems, NLP, computer vision, reinforcement learning.

• Proficiency in Python and ML libraries: TensorFlow, PyTorch, scikit-learn, Keras, XGBoost, LightGBM.

• Experience with data processing and pipelines: Pandas, NumPy, SQL.

• Familiarity with cloud platforms: AWS, Azure, GCP, or on-prem ML infrastructure.

• Model deployment experience: Flask/FastAPI, Docker, Kubernetes, MLflow, or similar.

• Strong programming fundamentals: data structures, algorithms, and OOP.

• Experience with version control (Git) and collaborative software development.

• Ability to analyze and interpret complex data to drive actionable insights.

• Understanding of ML system monitoring, evaluation, and debugging.

📌 Experience Requirements

• 2–5+ years of experience in machine learning or AI engineering.

• Hands-on experience building and deploying ML models in production.

• Experience with structured and unstructured data (tabular, text, image, time-series).

• Experience with MLOps, model monitoring, or pipeline automation is a plus.

• Experience working with cross-functional teams in an Agile/Scrum environment.