As a Machine Learning Engineer at Avrio, you will play a crucial role in designing, developing, and deploying scalable machine learning models that drive our product innovation and enhance business outcomes for our clients. You will collaborate closely with the founding team and software engineers, contributing to the full machine learning development lifecycle from ideation and data collection to model training, optimization, and deployment. This is an excellent opportunity to work with cutting-edge technologies and make a significant impact on the technical direction of our AI-driven solutions.

Responsibilities

Design, develop, and deploy machine learning models to enhance product capabilities.
Implement and optimize data pipelines to collect, clean, and preprocess structured and unstructured data.
Apply machine learning algorithms and deep learning techniques for various business use cases, such as predictive analytics, recommendation systems, NLP, and computer vision.
Leverage Python and ML frameworks (e. g., TensorFlow, PyTorch, Scikit-Learn) to develop scalable and efficient AI solutions.
Work with relational (PostgreSQL) and non-relational databases (CouchDB) to store, query, and manage large-scale datasets.
Develop and deploy machine learning models using cloud platforms (AWS) and containerization tools (Docker, Kubernetes).
Implement MLOps best practices, including CI/CD pipelines for model training, monitoring, and deployment.
Collaborate with software developers and data engineers to integrate ML models into production environments.
Write and maintain unit tests and integration tests to ensure the quality and reliability of AI systems.

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field (or equivalent experience).
1+ years of experience in machine learning, data science, or AI-focused software development.
Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-Learn, etc. ).
Solid understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning) and deep learning architectures (CNNs, RNNs, Transformers).
Experience in building scalable data pipelines for preprocessing and feature engineering.
Strong background in OOP principles and software engineering best practices.
Experience with cloud platforms (AWS, GCP, or Azure) and deploying models in production environments.
Familiarity with MLOps practices, including model versioning, monitoring, and CI/CD pipelines.
Knowledge of RESTful APIs and GraphQL services, with experience in FastAPI being a plus.
Strong problem-solving skills and the ability to work independently as well as in a team.
This full-time role offers the chance to work on impactful AI-driven projects in a dynamic and growth-focused environment.

This job was posted by Harshit Rai from Avrio Energy.

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