AI Developer

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.

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.

Required Qualifications & Skills

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.