Machine Learning Engineer - Python/Tensorflow (3-5 yrs)

Job Summary :

We are seeking a highly motivated and experienced Machine Learning Engineer to join our growing team.

You will play a crucial role in developing, optimizing, and deploying machine learning models that power our [product/service].

The ideal candidate will have a strong understanding of machine learning principles, experience with various ML frameworks and tools, and a proven track record of building and deploying scalable ML solutions.

You will collaborate closely with other engineers and data scientists to solve challenging problems and deliver impactful results.

Primary Responsibilities :

Model Development & Optimization :

- Design, develop, and optimize machine learning models for various tasks, including training, inference, and deployment.

- This includes selecting appropriate algorithms, tuning hyperparameters, and evaluating model performance.

Data Preprocessing & Feature Engineering :

- Preprocess, clean, and engineer features from diverse data sources, both structured and unstructured.

- This involves handling missing data, transforming variables, and creating new features to improve model accuracy and performance.

Performance Optimization & Scalability :

- Optimize model performance for speed and accuracy, ensuring scalability in production environments.

- This includes addressing issues related to memory management, computational efficiency, and distributed processing.

Production Integration & Deployment :

- Collaborate with DevOps teams to seamlessly integrate ML models into production workflows.

- This involves containerization, deployment orchestration, and monitoring model performance in real-time.

Model Versioning & Management :

- Utilize tools like MLflow, DVC, or similar platforms for model versioning, tracking experiments, and managing model lifecycle.

Data Exploration & Analysis :

- Explore and analyze large datasets to identify patterns, insights, and potential features for model development.

Collaboration & Communication :

- Collaborate effectively with other engineers, data scientists, and product managers to define requirements, discuss technical challenges, and communicate results.

Research & Development :

- Stay up-to-date with the latest advancements in machine learning and contribute to research and development efforts to improve our ML capabilities.

Key Skills Required :

- Experience : 3+ years of hands-on experience in building and deploying machine learning models in production environments.

- Programming Languages : Strong programming skills in Python.

- ML Frameworks & Libraries : Proficiency in TensorFlow, PyTorch, Scikit-learn, or other relevant ML frameworks and libraries.

- Feature Engineering : Deep understanding and practical experience with feature engineering techniques.

- Model Evaluation & Optimization : Expertise in model evaluation metrics, hyperparameter tuning, and model optimization strategies.

- Model Versioning Tools : Familiarity with MLflow, DVC, or similar model versioning and experiment tracking tools.

- Big Data Technologies : Experience working with large-scale datasets and distributed computing frameworks like Spark.

- Cloud Computing : Exposure to cloud-based ML services, particularly AWS SageMaker, or similar platforms (e.g, Google Cloud AI Platform, Azure Machine Learning).

- DevOps & MLOps : Understanding of DevOps principles and experience with MLOps practices for deploying and managing ML models in production.

- Communication & Collaboration : Excellent communication and collaboration skills to work effectively in a team environment.

Preferred Qualifications :

- Master's or Ph.in Computer Science, Machine Learning, or a related field.

- Experience with specific ML domains (e.g, NLP, Computer Vision, Recommender Systems).

- Contributions to open-source ML projects.

- Publications in relevant conferences or journals