Senior Artificial Intelligence Leader

We are seeking a seasoned AI leader to spearhead the design, development, and deployment of large-scale AI solutions. The ideal candidate will bridge the gap between business requirements and technical implementation, with deep expertise in generative AI and modern MLOps practices.

• Key Responsibilities:

• AI Solution Design & Implementation

• Design end-to-end AI systems leveraging large language models and generative AI technologies, ensuring scalability and performance meet business objectives.

• Design Scalable, Production-Ready AI Applications

• Design scalable, production-ready AI applications that meet business requirements and performance expectations, streamlining deployment and maintenance processes.

• Evaluate & Integrate LLM APIs

• Evaluate and integrate leading LLM APIs (OpenAI, Anthropic Claude, Google Gemini) to leverage their capabilities and stay current with latest advancements.

• Establish Best Practices

• Develop and promote best practices for prompt engineering, model selection, and AI system optimization, fostering a culture of excellence and innovation within the organization.

• Model Development & Fine-tuning

• Fine-tune open-source models (Llama, Mistral) for specific business use cases, ensuring optimal performance and efficiency.

• Implement Custom Training Pipelines

• Design and implement custom training pipelines and evaluation frameworks to support data-driven decision making and continuous improvement.

• Optimize Model Performance

• Optimize model performance, latency, and cost for production environments, ensuring seamless integration and scalability.

• Stay Current with Latest Models

• Stay up-to-date with the latest model architectures, fine-tuning techniques, and industry trends to drive innovation and growth.

• Infrastructure & Deployment

• Deploy and manage AI models at enterprise scale using containerization (Docker) and orchestration (Kubernetes), ensuring efficient resource utilization and high availability.

• Build Robust APIs

• Design and develop robust, scalable APIs using FastAPI and similar frameworks to support seamless data exchange and integration.

• MLOps Pipelines

• Design and implement MLOps pipelines for model versioning, monitoring, and continuous deployment, ensuring predictable and reliable outcomes.

• Business & Technical Leadership

• Collaborate with stakeholders to translate complex business requirements into technical solutions, driving alignment and success.

• Provide Technical Guidance

• Provide expert technical guidance and mentorship to development teams, promoting knowledge sharing and skill development.

• Conduct Feasibility Assessments

• Conduct thorough feasibility assessments and technical due diligence for AI initiatives, ensuring informed decision making and project success.

• Required Qualifications

• Experience

• 7+ years of experience in machine learning engineering or data science, with a strong track record of delivering large-scale ML solutions.

• Proven Track Record

• A proven track record of delivering successful AI projects, with expertise in LLM APIs, model fine-tuning, and MLOps pipelines.

• Technical Skills

• Expert-level proficiency with LLM APIs (OpenAI, Claude, Gemini), including hands-on experience with model fine-tuning and API integration.

• Fine-tune Transformer Models

• Hands-on experience fine-tuning transformer models (Llama, Mistral) for specific business use cases, ensuring optimal performance and efficiency.

• Strong Proficiency in FastAPI

• Strong proficiency in FastAPI, Docker, and Kubernetes, with experience designing and deploying scalable APIs and microservices.

• Experience with ML Frameworks

• Experience with popular ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers), including expertise in model development, deployment, and maintenance.

• Proficiency in Python

• Proficiency in Python and modern software development practices, with expertise in coding standards, testing, and debugging.

• Cloud Platforms

• Experience with cloud platforms (AWS, GCP, Azure) and their AI/ML services, including expertise in deploying and managing AI models at scale.

• Core Competencies

• Strong understanding of transformer architectures, attention mechanisms, and modern NLP techniques, with expertise in applying these concepts to real-world problems.

• MLOps Tools

• Experience with MLOps tools and practices (model versioning, monitoring, CI/CD), including expertise in designing and implementing automated pipelines and workflows.

• Translate Business Requirements

• Ability to translate complex business requirements into technical solutions, with expertise in communicating technical concepts to non-technical stakeholders.

• Problem-solving Skills

• Strong problem-solving skills and architectural thinking, with expertise in breaking down complex problems into manageable components and developing effective solutions.

• Preferred Qualifications

• Experience with vector databases and retrieval-augmented generation (RAG) systems, as well as knowledge of distributed training and model parallelization techniques.

• Distributed Training

• Knowledge of distributed training and model parallelization techniques, with experience in scaling AI workloads and optimizing performance.

• Model Quantization

• Experience with model quantization and optimization for edge deployment, including expertise in reducing model size and improving inference performance.

• Ai Safety

• Familiarity with AI safety, alignment, and responsible AI practices, including expertise in identifying and mitigating potential risks and biases.

• Domain Experience

• Experience in specific domains (finance, healthcare, legal), with expertise in applying AI and ML techniques to solve real-world problems.

• Advanced Degree

• Advanced degree in Computer Science, AI/ML, or related field, with a strong foundation in mathematics, statistics, and computer programming.