Machine Learning Engineer

Overview :

We are seeking a Machine Learning Engineer to design, develop, and deploy intelligent solutions using machine learning techniques. The ideal candidate will have hands-on experience in ML model development, data preprocessing, and deployment, along with proficiency in programming and ML frameworks.

Key Responsibilities :

- Design, develop, and implement machine learning models for classification, regression, NLP, recommendation systems, or computer vision tasks.

- Perform data preprocessing, feature engineering, and exploratory data analysis (EDA) to prepare datasets for modeling.

- Develop ML pipelines and integrate models into production environments using APIs or cloud services.

- Optimize and fine-tune models for accuracy, efficiency, and scalability.

- Collaborate with data engineers, software developers, and business stakeholders to define requirements and deliver AI-driven solutions.

- Monitor model performance and retrain/update models as necessary.

- Document workflows, models, and processes to ensure reproducibility and knowledge sharing.

Required Technical Skills :

- Programming Languages : Python (primary), R or Java (optional).

- ML Frameworks : TensorFlow, PyTorch, scikit-learn, Keras.

- Data Manipulation & Analysis : Pandas, NumPy, Matplotlib, Seaborn.

- Databases : SQL, NoSQL (MongoDB, Cassandra, or equivalent).

- Deployment & Cloud : AWS SageMaker, Azure ML, or GCP AI Platform.

- Algorithms : Supervised and unsupervised learning, NLP, deep learning, and reinforcement learning basics.

- Tools : Git, Jupyter Notebooks, Docker, and CI/CD pipelines for ML.

Preferred Skills :

- Experience with MLOps practices, model monitoring, and automated retraining.

- Knowledge of big data tools like Spark, Hadoop, or Kafka for ML pipelines.

- Familiarity with computer vision, NLP, or recommendation systems.

- Exposure to containerization and orchestration (Docker, Kubernetes) for ML workloads.

- Strong analytical, problem-solving, and communication skills to interact with cross-functional teams.