Artificial Intelligence Developer

We are seeking an experienced and results-oriented AI Developer to join our team. In this role, you will be tasked with developing, deploying, and optimizing AI and machine learning models to address real-world business challenges. Collaboration with cross-functional teams will be essential to deliver scalable and ethical AI solutions utilizing cutting-edge tools and technologies. With a minimum of 2 years of experience, your key responsibilities will encompass various aspects: Data Engineering & Preprocessing - Collaborate with data scientists and engineers to acquire, clean, and preprocess extensive datasets. - Conduct feature engineering and data selection to enhance model inputs. AI Model Development & Implementation - Design, construct, and validate machine learning and deep learning models, including CNNs, RNNs/LSTMs, Transformers, NLP and computer vision models, reinforcement learning agents, and classical ML techniques. - Develop models tailored to specific business challenges within domains. Performance Optimization & Scalability - Enhance models for performance, latency, scalability, and resource efficiency. - Ensure models are ready for production in real-time applications. Deployment, MLOps & Integration - Establish and maintain MLOps pipelines for model deployment, monitoring, and retraining. - Utilize Docker, Kubernetes, and CI/CD tools for containerization and orchestration. - Deploy models on cloud platforms (AWS, Azure, GCP) or on-site infrastructure. - Integrate models into systems and applications via APIs or model-serving frameworks. Testing, Validation & Continuous Improvement - Implement testing strategies such as unit testing, regression testing, and A/B testing. - Continuously enhance models based on user feedback and performance metrics. Research & Innovation - Stay informed about AI/ML advancements, tools, and techniques. - Experiment with novel approaches to drive innovation and maintain a competitive edge. Collaboration & Communication - Collaborate closely with engineers, product managers, and subject matter experts. - Document model architecture, training processes, and experimental results. - Clearly communicate complex technical subjects to non-technical stakeholders. Ethical AI Practices - Support and implement ethical AI practices focusing on fairness, transparency, and accountability. Required Qualifications & Skills Core Technical Skills - Proficiency in Python and experience with libraries like TensorFlow, PyTorch, Keras, and Scikit-learn. - Solid grasp of ML/DL architectures including CNNs, RNNs/LSTMs, and Transformers. - Proficient in data manipulation using Pandas, NumPy, and SciPy. MLOps & Deployment Experience - Experience with MLOps tools such as MLflow, Kubeflow, and DVC. - Familiarity with Docker, Kubernetes, and CI/CD pipelines. - Demonstrated ability to deploy models on cloud platforms (AWS, Azure, or GCP). Software Engineering & Analytical Thinking - Strong foundation in software engineering principles: Git, unit testing, and code optimization. - Strong analytical mindset with experience handling large datasets. Communication & Teamwork - Excellent written and verbal communication skills. - Collaborative team player with prior 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 such as Pinecone, FAISS, and 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.,