AI/ML Platform Engineer(4+ Exp.)

Avenoir Technologies; Bengaluru; Hybride; INR 1 500 000 - 3 500 000; Plein temps

Résumé du poste

Avenoir Technologies is seeking an AI/ML Platform Engineer to design, develop, implement, and deploy scalable AI/ML solutions. The role emphasizes hands-on Python programming, ML model development, and production-grade deployment across hybrid/remote environments.

You'll implement MLOps practices, build data pipelines, and collaborate with cross-functional teams to translate business needs into robust AI/ML capabilities using TensorFlow, PyTorch, and cloud platforms.

Qualifications

• BS/MS in CS/IT/AI or related field with strong fundamentals.
• Hands-on experience in Python and ML model development.
• Experience with ML libraries and deployment to production.
• Knowledge of data preprocessing, feature engineering, and model evaluation.
• Familiarity with MLOps, CI/CD, and cloud platforms.

Responsabilités

• Design, develop, and deploy ML models for business problems.
• Implement MLOps for deployment, monitoring, and governance.
• Build data pipelines and feature engineering workflows.
• Develop and deploy Deep Learning models using TensorFlow/PyTorch.
• Collaborate with teams to translate requirements into AI/ML solutions.

Connaissances

Python programming

ML algorithms & model development

Supervised learning

Unsupervised learning

Reinforcement learning

Deep learning

Neural networks

Computer vision

SQL

REST APIs

Cloud platforms (AWS/Azure/GCP)

Formation

Bachelor's or Master’s in CS/IT/AI

Outils

Scikit-learn

TensorFlow

PyTorch

Description du poste

Job Title: AI/ML PlatformEngineer

Experience: 4-5 Years

Location: Pune / Bangalore / NCR (Hybrid/Remote)

Employment Type: Full-Time

About the Role

We are looking for a passionate and skilled AI/ML Engineer to design, develop, implement, and deploy scalable Artificial Intelligence and Machine Learning solutions. The ideal candidate will have strong hands-on experience in Python programming, machine learning algorithms, deep learning, data processing, model development, and deployment of AI/ML applications.

Key Responsibilities

• Design, develop, and implement Machine Learning models for real-world business problems.
• Implement MLOps practices for model deployment, monitoring, governance, and lifecycle management.
• Build, train, evaluate, and optimize supervised and unsupervised learning models.
• Develop predictive models, classification, regression, clustering, and recommendation systems.
• Work with structured and unstructured datasets for data analysis and model development.
• Perform model performance analysis, troubleshooting, and continuous improvement activities.
• Implement feature engineering, data preprocessing, and model validation techniques.
• Develop and deploy Deep Learning models using frameworks such as TensorFlow and PyTorch.
• Create data pipelines and workflows to support AI model development and production operations.
• Integrate AI/ML models with enterprise applications, REST APIs, and cloud platforms.
• Optimize model performance, scalability, accuracy, and efficiency.
• Collaborate with business and technical teams to translate requirements into AI/ML solutions.

Required Skills

• Strong experience with Python programming.
• Hands-on experience in Machine Learning algorithms and model development.
• Good understanding of supervised, unsupervised, and reinforcement learning concepts.
• Experience with Machine Learning libraries such as Scikit-learn, TensorFlow, and PyTorch.
• Strong knowledge of Data Preprocessing, Feature Engineering, and Model Evaluation.
• Experience with Deep Learning, Neural Networks, and statistical modeling.
• Understanding of and Computer Vision concepts.
• Strong SQL knowledge and experience working with databases.
• Experience with REST APIs and model deployment.
• Knowledge of cloud platforms such as AWS, Azure, or GCP.
• Understanding of model optimization, performance tuning, and scalability.

Good to Have

• Fine-tuning and model optimization experience.
• Experience with Generative AI, LLMs, and Prompt Engineering.
• Knowledge of LangChain, LlamaIndex, or similar AI frameworks.
• Experience with MLOps, MLflow, Docker, Kubernetes, and CI/CD pipelines.
• Knowledge of RAG architectures and vector databases.
• Experience with model monitoring, versioning, and production deployment.
• Knowledge of Big Data technologies and distributed computing.

Education

Bachelors or Masters degree in Computer Science, Information Technology, Artificial Intelligence, or related field.