Sr. AI/ML Engineer

Armakuni; Ahmedabad; On-site; USD 681 - 1,136; Full time

Job summary

Join a forward-thinking company as a Machine Learning Engineer, where you'll design and develop innovative machine learning pipelines for diverse applications, including classification, regression, and natural language processing. This role involves experimenting with cutting-edge algorithms and frameworks like TensorFlow and PyTorch, while also focusing on computer vision tasks. Collaborate with talented data scientists and software engineers to ensure the successful deployment of machine learning solutions. If you're passionate about leveraging AI to make a significant impact, this opportunity is perfect for you.

Qualifications

• Experience in designing and developing machine learning pipelines.
• Proficient in various machine learning algorithms and frameworks.

Responsibilities

• Design and develop machine learning pipelines for classification and NLP.
• Integrate and monitor machine learning models in production systems.

Skills

Machine Learning

Natural Language Processing (NLP)

Computer Vision

Data Pre-processing

Model Optimization

Cloud Platforms (AWS, GCP, Azure)

Collaboration Skills

Communication Skills

Tools

TensorFlow

PyTorch

scikit-learn

LangChain

Job description

Job Responsibilities

• Design and develop machine learning pipelines for various tasks, including classification, regression, and natural language processing (NLP).
• Implement and experiment with different machine learning algorithms and techniques (e.g., supervised learning, unsupervised learning, deep learning).
• Pre-process and clean large datasets for model training and evaluation.
• Train, evaluate, and optimize machine learning models using frameworks like TensorFlow, PyTorch, scikit-learn, and LangChain.
• Integrate machine learning models into production systems and monitor their performance.
• Design and develop machine learning pipelines for computer vision tasks, including object detection, image classification, and image segmentation.
• Implement and experiment with different machine learning algorithms and techniques specific to computer vision, such as convolutional neural networks (CNNs).
• Collaborate effectively with data scientists, software engineers, and other stakeholders to ensure the successful development and deployment of machine learning solutions, particularly focusing on computer vision and LLM applications.
• Communicate complex technical concepts to non-technical audiences.
• Experience with cloud platforms (e.g., AWS, GCP, Azure) for deploying machine learning models.
• Utilize database knowledge to efficiently store, retrieve, and manage large datasets used for training and evaluating machine learning models.
• Build and maintain a GenAI based platform.
• Build AI Agents to propose actions for Food Security/Strategic Commodity Reserves team and models.
• Lead the architecture of a resilient, secure, and scalable GenAI platform.
• Architect and build an AI Agents module to propose actions for Food Security/Strategic Commodity Reserves team and models.