Artificial Intelligence Specialist

Lead Engineer-AI/ML:

About Us:

Headquartered in Sunnyvale, with offices in Dallas & Hyderabad, Fission Labs is a leading software development company,specializing in craftingflexible, agile, and scalable solutions that propelbusinesses forward. With a comprehensive range of services, including product development, cloud engineering, big data analytics, QA, DevOps consulting, and AI/ML solutions, we empower clientsto achieve sustainable digital transformation that aligns seamlessly with their business goals.

Role and Responsibilities

• Design, develop, and deploy advanced AI models with a focus on generative AI, including transformer architectures (e.g., GPT, BERT, T5) and other deep learning models used for text, image, or multimodal generation.
• Work with extensive and complex datasets,performing tasks such as cleaning, preprocessing, and transforming data to meet quality and relevance standards for generative model training.
• Collaborate with cross-functional teams (e.g., product,engineering, data science)to identify project objectives and create solutions using generative AI tailored to business needs.
• Implement, fine-tune, and scale generative AI models in production environments, ensuring robust model performance and efficient resourceutilization.
• Develop pipelines and frameworks for efficient data ingestion, modeltraining, evaluation, and deployment, including A/B testingand monitoring of generative models in production.
• Stay informedabout the latestadvancements in generative AI research, techniques, and tools, applying new findings to improve model performance, usability, and scalability.

• Document and communicate technical specifications, algorithms, and project outcomes to technical and non-technical stakeholders, with an emphasis on explainability and responsible AI practices.

Qualifications Required

• Educational Background: Bachelor’s or Master’s degree in ComputerScience, Data Science, AI/ML, or a relatedfield. Relevant Ph.D.or research experience in generative AI is a plus.
• Experience: 8-11 years of experience in machine learning, with 2+ years in designing

and implementing generative AI models or working specifically with transformer-based models.

Technical Expertise:

• Proficiency in Python, along with experience in libraries and frameworks central to generative AI, such as Hugging Face Transformers, PyTorch,and TensorFlow.
• Strong understanding of transformer architectures, language models, and generative modelingtechniques (e.g., GANs,VAEs, autoregressive models).
• Expertise in data processing techniques for training large language models, including handling unstructured data, tokenization, and feature extraction.
• Familiarity with MLOps practices and tools (e.g.,Docker, Kubernetes, MLflow)for deploying and managing large-scale models in production.
• Experience with cloud platforms (AWS, GCP, Azure) and GPU/TPU resources for training and fine-tuning large models.

Core Skills:

• Machine Learning: Strong foundation in machine learningalgorithms, deep learning, generative AI techniques.
• Programming: Proficient in Python, with knowledge of SQL for data handling and retrieval.
• Data Engineering: Experience with data preprocessing, feature engineering, and data transformation specific to large and complexdatasets.
• Model Evaluation: Knowledge of model evaluation metrics and techniques for generative models, especially for text generation, image synthesis, or multimodal AI.

Soft Skills:

• Strong analytical and problem-solving skillswith a high level of attention to detail.
• Excellent communication skills, with the ability to explain complex generative AI concepts to both technical and non-technical audiences.
• Collaborative mindset with the capability to work effectively in cross-functional teams.

Skills and Experience Required:

• Generative AI: Transformer Models, GANs, VAEs, Text Generation, Image Generation
• Machine Learning: Algorithms, Deep Learning, Neural Networks
• Programming: Python,SQL; familiarity with libraries such as HuggingFace Transformers, PyTorch, TensorFlow
• MLOps: Docker,Kubernetes, MLflow, Cloud Platforms (AWS, GCP, Azure)
• Data Engineering: Data Preprocessing, Feature Engineering, Data Cleaning

We Offer:

• Opportunity to work on technical challenges with global impact.
• Vast opportunities for self-development, including online university accessand sponsored certifications.
• Sponsored Tech Talks & Hackathons to foster innovation and learning.
• Generous benefits package including health insurance, retirement benefits, flexible work hours, and more.
• Supportive work environment with forums to explore passionsbeyond work.
• This role presents an exciting opportunity for a motivated individual to contribute to the development of cutting-edge solutionswhile advancing their career in a dynamic and collaborative environment.