AI Lead

What will you do

• AI Strategy & Roadmap:

  Define the AI roadmap aligned with business goals and emerging tech trends.

• Model Development & Optimization:

  Architect, train, and fine-tune AI/ML models, including LLMs, GANs, and deep learning frameworks (TensorFlow, PyTorch, JAX, etc.).

• Scalability & Performance:

  Optimize AI pipelines for performance, efficiency, and scalability in production environments.

• Team Leadership:

  Lead, mentor, and scale a team of AI engineers and researchers.

• Cross-functional Collaboration:

  Work closely with engineering, product, and customer teams to integrate AI into SaaS products.

• Data Strategy:

  Build robust data pipelines and ensure high-quality, annotated datasets for training and validation.

• AI Innovation:

  Keep Spyne at the forefront of AI by exploring new techniques in computer vision, NLP, and GenAI.

• Stakeholder Management:

  Communicate AI strategy, progress, and impact effectively to leadership and investors.

What will make you successful in this role

• Technical Expertise:

  Strong experience in computer vision, deep learning (CNNs, GANs, transformers), and Generative AI.

• Programming Proficiency:

  Expertise in Python, TensorFlow, PyTorch, OpenCV, and AI/ML deployment frameworks.

• Scalability & Cloud AI

  : Experience deploying AI models at scale using AWS, Azure, or GCP.

• Team Management:

  Proven ability to lead and scale AI teams, drive technical excellence, and mentor engineers.

• Problem-Solving Mindset:

  Ability to break down complex problems and deliver AI solutions with real business impact.

• Stakeholder Management:

  Strong collaboration skills with product and business teams to drive AI adoption.

What you must have

• 7+ years of experience in AI/ML, with at least 3 years in a leadership role.
• Expertise in

  LLMs, Generative AI, Computer Vision, NLP, and Deep Learning

  .
• Strong proficiency in AI frameworks like TensorFlow, PyTorch, JAX, and Hugging Face.
• Experience deploying AI models in

  cloud environments (AWS, GCP, Azure)

  .
• Proven track record of building scalable AI solutions in a SaaS startup or enterprise environment.
• Hands-on experience with

  data pipelines, MLOps, and AI model optimization

  .
• Strong coding skills in

  Python, C++, or Java

  .
• Excellent team management and stakeholder communication skills.