Artificial Intelligence Engineer

Awign Expert; Dadri; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

Awign Expert is seeking an experienced AI Developer to design, develop, deploy, and optimize AI/ML models that solve real-world business problems. You will work with cross-functional teams to build scalable, ethical AI solutions using state-of-the-art tools and practices.

The role emphasizes data engineering, model development across CNNs, RNNs/LSTMs, Transformers, NLP and CV, plus deployment via MLOps on cloud platforms (AWS/Azure/GCP) or on-premises and API integrations.

Qualifications

• 6+ years of experience in AI/ML development and deployment.

Responsibilities

• Data engineering and preprocessing to source, clean, and prepare large datasets.
• Design, build, and validate ML/DL models (CNNs, RNNs/LSTMs, Transformers, NLP, CV).
• Optimize models for performance, latency, and scalability.
• Build MLOps pipelines for deployment, monitoring, and retraining with Docker/Kubernetes.
• Deploy models on cloud or on-premises and integrate via APIs.

Skills

Python

ML/DL

Data preprocessing

Model deployment

MLOps

Tools

TensorFlow

PyTorch

Keras

scikit-learn

Pandas

NumPy

SciPy

MLflow

Kubeflow

DVC

Docker

Kubernetes

CI/CD

Job description

We are looking for an experienced and results-driven AI Developer to join our team. The ideal candidate will be responsible for developing, deploying, and optimizing AI and machine learning models to solve real-world business problems. You will collaborate with cross-functional teams to deliver scalable and ethical AI solutions using state-of-the-art tools and technologies.

Location: Onsite - Noida, India

Experience: Minimum 6+ years experience

Key Responsibilities:

Data Engineering & Preprocessing Collaborate with data scientists and engineers to source, clean, and preprocess large datasets. Perform feature engineering and data selection to improve model inputs.

AI Model Development & Implementation Design, build, and validate machine learning and deep learning models, including: Convolutional Neural Networks (CNNs) Recurrent Neural Networks (RNNs/LSTMs) Transformers NLP and computer vision models Reinforcement learning agents Classical ML techniques Develop models tailored to domain-specific business challenges.

Performance Optimization & Scalability Optimize models for performance, latency, scalability, and resource efficiency. Ensure models are production-ready for real-time applications.

Deployment, MLOps & Integration Build and maintain MLOps pipelines for model deployment, monitoring, and retraining. Use Docker, Kubernetes, and CI/CD tools for containerization and orchestration.

Deploy models on cloud platforms (AWS, Azure, GCP) or on-premise infrastructure.

Integrate models into systems and applications via APIs or model-serving frameworks. Testing, Validation & Continuous Improvement Implement testing strategies like unit testing, regression testing, and A/B testing. Continuously improve models based on user feedback and performance metrics.

Research & Innovation Stay up to date with AI/ML advancements, tools, and techniques. Experiment with new approaches to drive innovation and competitive advantage. Collaboration & Communication Work closely with engineers, product managers, and subject matter experts. Document model architecture, training processes, and experimental findings. Communicate complex technical topics to non-technical stakeholders clearly.

Ethical AI Practices Support and implement ethical AI practices focusing on fairness, transparency, and accountability.

Core Technical Skills Proficient in Python and experienced with libraries such as TensorFlow, PyTorch, Keras, Scikit-learn. Solid understanding of ML/DL architectures (CNNs, RNNs/LSTMs, Transformers). Skilled in data manipulation using Pandas, NumPy, SciPy. MLOps & Deployment Experience Experience with MLOps tools like MLflow, Kubeflow, DVC. Familiarity with Docker, Kubernetes, and CI/CD pipelines. Proven ability to deploy models on cloud platforms (AWS, Azure, or GCP). Software Engineering & Analytical Thinking Strong foundation in software engineering: Git, unit testing, and code optimization. Strong analytical mindset with experience working with large datasets. Communication & Teamwork Excellent communication skills, both written and verbal. Collaborative team player with experience in agile environments.

Domain-Specific Experience:

Experience applying AI in sectors like healthcare, finance, retail, manufacturing, or customer service. Specialized knowledge in NLP, computer vision, or reinforcement learning. Academic & Research Background Strong background in statistics and optimization.