Machine Learning Research Engineer

Who are we?
Founded in 2014 by Khadim Batti and Vara Kumar, Whatfix is a leading global B2B SaaS provider and the largest pure-play enterprise digital adoption platform (DAP). Whatfix empowers companies to maximize the ROI of their digital investments across the application lifecycle, from ideation to training to the deployment of software. Driving user productivity, ensuring process compliance, and improving user experience of internal and customer-facing applications.
Spearheading the category with serial innovation and unmatched customer-centricity, Whatfix is the only DAP innovating beyond the category, positioning itself as a comprehensive suite for GenAI-powered digital adoption, analytics, and application simulation. Whatfix product suite consists of 3 products - Mirror, DAP and Analytics. This product suite helps businesses accelerate ROI on digital investments by streamlining application deployment across its lifecycle.

• Whatfix has seven offices across the US, India, UK, Germany, Singapore, and Australia and a presence across 40+ countries.
• Customers: 700+ enterprise customers, including over 85 Fortune 500 companies such as Shell, Microsoft, Schneider Electric, and UPS Supply Chain Solutions.
• Investors: Raised a total of ~$270 million. Most recently Series E round of $125 Million led by Warburg Pincus with participation from existing investor SoftBank Vision Fund 2
• Other investors include Cisco Investments, Eight Roads Ventures (A division of Fidelity Investments), Dragoneer Investments, Peak XV Partners, and Stellaris Venture Partners.

“Hustle Mode ON” is something we live by.

About the Role:

Whatfix is working on building an intelligent assistant that understands user actions and intent, acting as a helpful guide to enhance productivity. This assistant will anticipate user needs, provide actionable insights, and streamline task completion.

We are seeking a rockstar AI/ML Engineers who have experience in building world-class products. The ideal candidate will have a strong passion for leveraging AI and machine learning to create cutting-edge solutions that transform user experiences. If you thrive in solving complex problems, pushing the boundaries of AI/ML technology, and working collaboratively in a fast-paced environment, this role is for you!

Key Responsibilities:

• Develop advanced computer vision and state-of-the-art deep learning models to understand software applications and derive user intent.
• Research and implement ML and deep learning algorithms for production use.
• Build and maintain infrastructure for AI/ML systems, including model inference, automated (re-)training, monitoring, explainability, and more.
• Stay updated on cutting-edge AI research from leading labs by reading papers and experimenting with code.
• Assist AI product managers and business stakeholders in understanding the capabilities and limitations of AI for the products.
• Fine-tune, retrain, and scale existing model deployments.
• Conduct necessary ML tests and benchmarks for model validation.

Our Ideal candidate:

• Experience: 4+ years of expertise in machine learning.
• Deep Learning Expertise: Strong understanding of deep learning principles in both Computer Vision and Natural Language Processing (NLP).
• LLM Knowledge: Familiarity with LLM architectures like BERT and GPT, with hands-on experience fine-tuning these models for enhanced performance.
• Model Development: Proven experience in developing deep learning models, such as CNNs and Vision Transformers, for image-based tasks in production systems.
• Research and Application: Extensive experience in algorithms for image processing, content-based video/image analysis, object detection, segmentation, and tracking.
• Libraries: Proficiency in machine learning and deep learning libraries like PyTorch and Hugging Face.
• Technical Skills: Demonstrated ability to implement, improve, debug, and maintain machine learning models.

Nice to Have:

• Strong programming skills in Python.
• Expertise in optimization and debugging.
• Familiarity with version control systems such as Git.
• Self-motivated and responsible, with excellent written and verbal communication skills.
• Experience in handling and visualizing large datasets and creating performance reports.

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