Thoucentric - Applied Machine Learning Scientist - Computer Vision/NLP/LLM (3-8 yrs)

About Us :

Thoucentric is the Consulting arm of Xoriant, a prominent digital engineering services company with 5000+ employees. We are headquartered in Bangalore with presence across multiple locations in India, US, UK, Singapore & Australia Globally.

As the Consulting business of Xoriant, We help clients with Business Consulting, Program & Project Management, Digital Transformation, Product Management, Process & Technology Solutioning and Execution including Analytics & Emerging Tech areas cutting across functional areas such as Supply Chain, Finance & HR, Sales & Distribution across US, UK, Singapore and Australia. Our unique consulting framework allows us to focus on execution rather than pure advisory. We are working closely with marquee names in the global consumer & packaged goods (CPG) industry, new age tech and start-up ecosystem. Xoriant (Parent entity) started in 1990 and is a Sunnyvale, CA headquartered digital engineering firm with offices in the USA, Europe, and Asia. Xoriant is backed by ChrysCapital, a leading private equity firm. Our strengths are now combined with Xoriants capabilities in AI & Data, cloud, security and operations services proven for 30 years.

We have been certified as "Great Place to Work" by AIM and have been ranked as "50 Best Firms for Data Scientists to Work For".

We have an experienced consulting team of over 450+ world-class business and technology consultants based across six global locations, supporting clients through their expert insights, entrepreneurial approach and focus on delivery excellence. We have also built point solutions and products through Thoucentric labs using AI/ML in the supply chain space.

Job Description :

We are seeking a highly skilled Applied Machine Learning Scientist with a strong focus on advanced computer vision, natural language processing (NLP), and large language models (LLM). This role is ideal for an ML Scientist ready to develop and deploy cutting-edge solutions that address complex real-world challenges, bridging the gap between technical innovation and client needs.

Key Responsibilities :

- Advanced Model Development : Design, implement, and optimize computer vision, NLP, and large language models, applying advanced algorithms to solve complex client problems. Evaluate model suitability based on requirements and constraints, ensuring the selection of the most effective approach.

- Data Preprocessing and Feature Engineering : Perform thorough data preprocessing, feature engineering, and transformation tasks for image, text, and multi-modal data to maximize model performance and accuracy.

- Custom Model Tuning and Fine-Tuning LLMs : Leverage and fine-tune state-of-the-art NLP models, such as BERT, GPT, and other transformer-based architectures, adapting them to specific domain requirements. Apply transfer learning, domain adaptation, and few-shot techniques for customized model outputs.

- Computer Vision Solutions : Implement and optimize computer vision techniques, including image segmentation, object detection, classification, and image generation, using state-of-the-art architectures such as CNNs, YOLO, and vision transformers.

- Solution Strategy and Client Collaboration : Collaborate with clients to understand their unique needs, recommend solution strategies, and develop tailored machine learning and deep learning applications for NLP and computer vision tasks.

- Production-Ready Code and Pipeline Deployment : Write clean, efficient, production-grade Python code for deploying machine learning models as scalable cloud-based pipelines. Adhere to software engineering best practices, including version control, modular design, and testing.

- Cloud Platform and Model Deployment : Design and manage machine learning pipelines on cloud platforms (e.g., AWS, Azure, GCP), leveraging their services for model deployment, versioning, monitoring, and scaling.

- Result Analysis and Communication : Analyze and interpret model results, deriving actionable insights and translating complex findings for diverse audiences, from technical stakeholders to business users.

Requirements :

Required Skills and Qualifications :

- Computer Vision Expertise : Proven experience with computer vision techniques such as CNNs, object detection, image segmentation, and vision transformers. Proficiency in applying state-of-the-art models (e.g., YOLO, EfficientNet) for image-based tasks.

- NLP and Large Language Models : Advanced knowledge of NLP techniques and experience with transformer-based models like BERT, GPT, and T5. Skilled in fine-tuning and optimizing large language models (LLMs) for specific tasks and domains.

- Python and Software Engineering : Proficiency in Python programming with a strong understanding of object-oriented programming (OOP) principles and best practices for writing scalable, maintainable code.

- Cloud Platforms and Model Deployment : Hands-on experience with deploying machine learning solutions on cloud platforms (AWS, Azure, GCP), particularly for NLP and computer vision applications. Familiarity with MLOps tools for automated deployment and monitoring.

- Debugging, Optimization, and Best Practices : Excellent debugging skills with experience in code optimization, memory management, and troubleshooting in production environments.

- Client Engagement and Solution Design : Demonstrated ability to communicate effectively with clients, understand their needs, and provide clear technical solutions aligned with business goals.

Preferred Qualifications :

- Multi-Modal Modeling : Experience with multi-modal models that combine vision and NLP tasks, such as CLIP and other transformer-based architectures will be an added advantage.

- Experience with Distributed Computing and Big Data : Familiarity with distributed computing frameworks and big data tools, such as Spark, and Databricks, for handling large datasets in training pipelines.

- Innovation and Problem-Solving : Proactive, solution-focused mindset with a passion for staying at the forefront of ML advancements in computer vision and NLP.

This role is perfect for an ML Scientist with a passion for NLP, computer vision, and deploying innovative solutions using LLMs. If you're ready to leverage these advanced tools to solve complex challenges and deliver client-focused outcomes, we encourage you to apply.

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