Machine Learning Engineer

Overview

One of Our Client is looking for a AI/ML Engineer with 4 to 10 years of experience.

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As an AI/ML Engineer and play a pivotal role in designing, developing, deploying, and maintaining cutting-edge machine learning models and AI-powered systems. This position is crucial for transforming data into intelligent, scalable solutions that drive innovation and improve our products. You will collaborate closely with product managers, data engineers, and domain experts to deliver impactful results.

Key Responsibilities:

• Design, develop, and deploy machine learning models for real-world applications.
• Build robust data pipelines for training, evaluation, and inference.
• Implement and optimize machine learning algorithms for supervised, unsupervised, and reinforcement learning tasks.
• Fine-tune and deploy large language models (LLMs) and deep learning models to enhance our AI capabilities.
• Integrate ML models seamlessly into production systems through APIs and microservices.
• Monitor model performance, detect drift, and address retraining needs to ensure optimal accuracy.
• Conduct rigorous experiments, A/B testing, and model evaluation to validate and improve performance.
• Optimize models for performance, scalability, and cost-effectiveness.
• Document models, workflows, and technical decisions clearly and comprehensively.
• Stay current with the latest advancements in AI, ML, and data science to drive innovation.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• 3+ years of experience in AI/ML engineering.
• Strong proficiency in Python and essential ML libraries such as NumPy, Pandas, and Scikit-learn.
• Hands-on experience with deep learning frameworks like TensorFlow, PyTorch, or JAX.
• Solid understanding of machine learning algorithms, statistical modeling, and data structures.
• Proven experience deploying models using REST APIs or cloud services.
• Knowledge of SQL and experience with data handling at scale.
• Familiarity with version control systems (Git) and CI/CD pipelines.

Preferred Qualifications/Good to Have:

• Experience with cloud platforms such as AWS, GCP, or Azure.
• Experience with MLOps tools like MLflow, Kubeflow, Airflow, or Weights & Biases.
• Knowledge of Natural Language Processing (NLP), computer vision, or recommender systems.
• Experience working with large datasets and distributed systems (e.g., Spark, Ray).
• Familiarity with Large Language Models (LLMs), prompt engineering, and vector databases.

What Makes This Opportunity Attractive:

• Growth Potential: Be at the forefront of AI innovation, contributing to cutting-edge projects with significant impact.
• Continuous Learning: Access opportunities for professional development and training to expand your skills in the rapidly evolving field of AI/ML.
• Impactful Role: Directly influence the development and deployment of AI solutions that solve real-world problems and improve our products.
• Collaborative Environment: Work alongside a talented and passionate team of engineers, data scientists, and product managers.