AI Developer (Fulltime, onsite in | Open to Indiabased candidates only)

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

Type : Full-time employee

Experience : Minimum 2 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.

Preferred

Advanced AI & LLM Expertise

Hands-on experience with LLMs (e.g., GPT, Claude, Mistral, LLaMA).

Familiarity with prompt engineering and Retrieval-Augmented Generation (RAG).

Experience with LangChain, LlamaIndex, and Hugging Face Transformers.

Understanding of vector databases (e.g., Pinecone, FAISS, Weaviate).

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.

Research publications in top AI / ML conferences (e.g., NeurIPS, ICML, CVPR, ACL) are a plus.