AI & Machine Learning Engineers

AI & Machine Learning (Junior Engineer and Engineer)

Key Responsibilities

·         Model Development: Design, implement, and train machine learning models using state-of-the-art algorithms and frameworks including TensorFlow, PyTorch, scikit-learn

·         Data Preparation: Process, clean, and transform large datasets for training and evaluation of ML models.

·         Feature Engineering: Identify and engineer relevant features to optimize model performance and accuracy.

·         Algorithm Optimization: Research and implement advanced algorithms to address specific use cases, including classification, regression, clustering, and anomaly detection.

·         Integration: Collaborate with software developers to integrate ML models into production systems and ensure seamless operation.

·         Performance Evaluation: Evaluate model performance using appropriate metrics and continuously optimize for accuracy, efficiency, and scalability.

·         MLOps: Assist in setting up and managing CI/CD pipelines for model deployment and monitoring in production environments.

·         Research and Development: Stay updated with the latest advancements in Gen AI AI/ML technologies and propose innovative solutions.

·         Collaboration: Work closely with data engineers, product teams, and stakeholders to understand requirements and deliver tailored ML solutions.

Requirements

Educational Background:                                                                                                                                                                      Bachelor in Engineering in Computer Science, Data Science, Artificial Intelligence, or a related field.

Experience:                                                                                                                                                                                                                                                                                                                                                             3 to 6 years of hands-on experience in developing and deploying machine learning models.

Technical Skills:

·         Strong proficiency in Python and ML libraries/frameworks (e.g., scikit-learn, TensorFlow, PyTorch).

·         Experience with data manipulation tools like Pandas, NumPy, and visualization libraries such as Matplotlib or Seaborn.

·         Familiarity with big data frameworks (Hadoop, Spark) is a plus.

·         Knowledge of SQL/NoSQL databases and data pipeline tools (e.g., Apache Airflow).

·         Experience with cloud platforms (AWS, Azure, Google Cloud) and their Gen AI AI/ML services.

·         Strong understanding of supervised and unsupervised learning, deep learning, and reinforcement learning.

·         Exposure to MLOps practices and model deployment pipelines.

·         Strong problem-solving and analytical skills.

·         Effective communication and teamwork abilities.

·         Ability to work in a fast-paced, collaborative environment.

Benefits

·         Impactful Role: Be at the forefront of AI innovation, shaping solutions that redefine supply chain risk management and beyond.

·         Dynamic Environment: Work in a collaborative, fast-paced startup culture with passionate and skilled professionals.

·         Growth Opportunities: Thrive in a company that values innovation, creativity, and professional development.

·         Competitive Benefits: Enjoy an attractive compensation package and opportunities for personal and career growth.