Staff Machine Learning Engineer
Conga
| Company | Conga |
| Category | Engineering |
| Location | India - Bangalore |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 30 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
A career that’s the whole package!
At Conga, we’ve built a community where our colleagues can thrive. Here you’ll find opportunities to innovate and support growth through individual and team development, all within an environment where every voice is heard.
Conga lines up commercial operations so companies run as connected, smarter businesses. By unifying the people and processes that drive commerce, Conga aligns pricing, quoting, contracting, rebates, and communications so teams stay in sync and buyers keep moving forward. The result is trusted decisions, consistent buyer experiences, and profitable growth. More than 10,000 customers worldwide, including over 50% of the Fortune 100®, trust Conga when commercial complexity is high and global impact is on the line.
Job Title: Staff Machine Learning Engineer Locations: Bangalore Reports to : Director
A quick snapshot …
This leadership role drives strategic decision-making and broad organizational impact by overseeing multiple projects and aligning ML initiatives with business goals. Responsibilities include owning and architecting end-to-end ML/AI solutions, integrating models into business applications, and managing larger machine learning solutions. The position exists to coordinate cross-team efforts, ensuring scalable and effective AI implementations with Engineering and PMs.
Why it’s a big deal…
This is a critical role for the department as it balances technical implementation with project leadership, leading small to medium-sized initiatives while owning specific components in a Machine Learning solution and mentoring with their expertise.
Are you the person we’re looking for?
Experience. You should have overall more than 8 years of industry experience with more than 5 years in AI/ML solutions and leading the design, development, and deployment of ML models while maintaining expert-level coding proficiency (20%)
Optimization . You are good at ML solutions, especially in Machine Learning and optimizing it by ensuring best practices through code reviews and mentorship, fostering technical excellence across the team (15%). You know how to optimize –and support production systems, enhance performance, scalability, and reliability of machine learning solutions (15%)
Collaboration. You know how to collaborate with Product Managers, scientists, and cross-functional teams to gather requirements, align on objectives, and drive seamless communication for project execution (25%)
Managing project . You deliver high-quality solutions by creating clear workflows, ensuring timely delivery, and representing the Science team in Operations meetings (25%)
Proficiency. You are proficient in Python programming, Manage ML Libraries and TensorFlow, PyTorch, XgBoost, Scikit-learn, Spark ML and code/model versioning in Git, MLFlow.
You also have proficiency either in Named Entity Recognition/Ontology OR Document search using BM25, Vector search and Re-rankers OR Recommendation systems — collaborative filtering, content-based and hybrid approaches, two-tower architecture, and learning-to-rank
Platforms. You have worked on Cloud computing platforms like Azure,databricks and know well to work on data analytics tool like Spark and Pandas.
Transformer models. You have Hands-on experience in fine-tuning transformer models (BERT, RoBERTa, LegalBERT, DeBERTa) using the HuggingFace ecosystem including PEFT/LoRA
Here’s what will give you an edge…
Architecture. You are proficient in Architecting and designing end-to-end ML solutions, e.g. can take a one-sentence business requirement and design the end-to-end SM to satisfy such requirement.
Track Record. You have strong track record of success in leading ML/AI initiatives from concept to completion
Added advantage. Having Prior exposure to NLP applicatio
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