
AI Developer
1 day ago
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 ResponsibilitiesData 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.
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.
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