Description:
We are seeking an AI/ML Engineer to lead the design, development, and deployment of innovative artificial intelligence and machine learning solutions. The ideal candidate will have extensive experience in building AI systems, a deep understanding of state-of-the-art technologies, and a passion for solving complex business challenges. You will collaborate with cross-functional teams to translate business requirements into scalable AI architectures while ensuring the efficiency, security, and performance of AI systems.
Responsibilities:
- AI Solution Design: Architect, design, and implement scalable AI/ML solutions tailored to meet business goals and user requirements.
- Model Development: Develop, fine-tune, and optimize machine learning models, generative AI systems, and other advanced algorithms to address specific problems.
- Performance Optimization: Evaluate and refine AI models and pipelines for maximum efficiency, scalability, and accuracy.
- AI Research: Stay updated on the latest trends, advancements, and breakthroughs in AI/ML, including generative AI, deep learning, and reinforcement learning.
- AI Deployment: Deploy and monitor AI models in production, ensuring systems are robust, secure, and maintainable.
- Integration: Collaborate with software engineers, data scientists, and stakeholders to seamlessly integrate AI capabilities into business processes and products.
- Cloud Architecture: Leverage cloud platforms (e.g., AWS, Google Cloud, Azure) for large-scale AI workloads, ensuring cost-effective and reliable solutions.
- Technical Leadership: Mentor team members and provide guidance on AI/ML best practices, coding standards, and emerging technologies.
- Compliance and Ethics: Ensure all AI systems comply with relevant data privacy, security, and ethical standards.
- Documentation: Prepare comprehensive documentation for AI/ML models, workflows, and system architectures for easy reference and maintenance.
Key Skills:
- Proven Expertise in AI/ML: Extensive experience with developing and deploying AI models, including large language models (LLMs), deep learning, computer vision, and natural language processing.
- Hands-on Experience with LLMs: Proficiency in working with open-source large language models, including fine-tuning, post-training, prompt engineering, and RAG (Retrieval-Augmented Generation) pipelines.
- Programming Mastery: Advanced programming skills in Python and familiarity with other languages such as R or Java. Experience with async programming, design patterns, and advanced data structures.
- AI/ML Frameworks: Hands-on experience with tools like TensorFlow, PyTorch, Keras, and LLM inference frameworks like llama.cpp and vLLM.
- Cloud Expertise: Proficiency in using cloud-based platforms (e.g., AWS, GCP, Azure) for AI/ML workflows, including GPU-based training and inference.
- Data Handling: Strong skills in data preprocessing, ETL pipelines, and large-scale data analysis for AI/ML applications.
- Version Control & Collaboration Tools: Expertise in tools like Git, Docker, and collaborative development environments.
- Prompt Engineering: Deep understanding of crafting, evaluating, and iterating effective prompts for generative AI systems.
- AI Ethics & Compliance: Knowledge of AI-related ethical guidelines, data privacy, and security regulations.
- Technical Knowledge: Must know AI/ML best practices, coding standards, and emerging technologies.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- 4+ years of experience in AI/ML development, deployment, and optimization.
- Strong knowledge of AI/ML concepts such as supervised and unsupervised learning, reinforcement learning, and generative AI.
- Proven ability to translate research and business goals into deployable AI systems.
- Excellent problem-solving and analytical skills.
- Strong communication skills to present findings to both technical and non-technical stakeholders.