3 Transformer Models Jobs

Roles 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 resource utilization. Develop pipelines and frameworks for efficient data ingestion, model training, evaluation, and deployment, including A/B testing and monitoring of generative models in production. Stay informed about the latest advancements in generative AI research, techniques, and tools, applying new findings to improve model performance, usability, and scalability. Documentandcommunicatetechnicalspecifications, algorithms, and project outcomes to technical and non-technical stakeholders, with an emphasis on explainability and responsible AI practices. Qualifications Required Educational Background: Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or a related field. Relevant Ph.D. or research experience in generative AI is a plus. Experience: 8-12 years of experience in machine learning, with 2+ years in designing and implementing generative AI models or working specifically with transformer-based models. Skills and Experience Required GenerativeAI: Transformer Models, GANs, VAEs, Text Generation, Image Generation Machine Learning: Algorithms, Deep Learning, Neural Networks Programming: Python, SQL; familiarity with libraries such as Hugging Face Transformers, PyTorch, Tensor Flow MLOps: Docker, Kubernetes, MLflow, Cloud Platforms (AWS, GCP, Azure) Data Engineering: Data Preprocessing, Feature Engineering, Data Cleaning Why you'll love working with us: Opportunity to work on technical challenges with global impact. Vast opportunities for self-development, including online university access and sponsored certifications. Sponsored Tech Talks &Hackathons to foster innovation and learning. Generous benefits package including health insurance, retirement benefits, flexible work hours, and more. Private and Confidential www.fissionlabs.com info@fissionlabs.com Supportive work environment with forums to explore passions beyond work. This role presents an exciting opportunity for a motivated individual to contribute to the development of cutting-edge solutions while advancing their career in a dynamic and collaborative environment.

We are hiring for our client, who is an Indian multinational technology services company based in Pune. It is primarily engaged in cloud computing, internet of things, endpoint security, big data analytics and software product engineering services. About Position : As a crucial member of our team, you'll play a pivotal role across the entire machine learning lifecycle, contributing to our conversational AI bots, RAG system and traditional ML problem solving for our observability platform. Your tasks will encompass both operational and engineering aspects, including building production-ready inference pipelines, deploying and versioning models, and implementing continuous validation processes. On the LLM side you'll fine-tune generative AI models, design agentic language chains, and prototype recommender system experiments. Role: AL ML Engineer Location: Bengaluru Experience : 2-6 years What You'll Do Fine-tuning generative AI models to enhance performance. Designing AI Agents for conversational AI applications. Experimenting with new techniques to develop models for observability use cases Building and maintaining inference pipelines for efficient model deployment. Managing deployment and model versioning pipelines for seamless updates. Developing tooling to continuously validate models in production environments. What we're looking for: 2-6 Years Demonstrated proficiency in software engineering design practices. Bachelor's or advanced degree in Computer Science, Engineering, Mathematics, or a related field. Advanced degree (Master's or Ph.D.) preferred. Experience working with transformer models and text embeddings. Proven track record of deploying and managing ML models in production environments. Familiarity with common ML/NLP libraries such as PyTorch, TensorFlow, HuggingFace Transformers, and SpaCy. Preferred experience developing production-grade applications in Python. Proficiency in Kubernetes and containers. Familiarity with concepts/libraries such as sklearn, kubeflow, argo, and seldon. • Expertise in Python, C++, Kotlin, or similar programming languages. Experience designing, developing, and testing scalable distributed systems. Familiarity with message broker systems (e.g., Kafka, RabbitMQ). Knowledge of application instrumentation and monitoring practices. Experience with ML workflow management, like AirFlow, Sagemaker, etc. Familiarity with the AWS ecosystem. Past projects involving the construction of agentic language chains. Benefits : Competitive salary and benefits package Culture focused on talent development with quarterly promotion cycles and company sponsored higher education and certifications Opportunity to work with cutting-edge technologies Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards Annual health check-ups Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents .

We are seeking a talented and experienced Machine Learning Engineer with a strong focus on Natural Language Processing (NLP). You will play a key role in developing, optimizing, and deploying state-of-the-art NLP solutions. You will collaborate with cross-functional teams to design scalable AI-driven applications that leverage the latest advancements in machine learning. Key Responsibilities: Design, develop, and implement NLP models using modern techniques like BERT, GPT, and other LLMs. Fine-tune pre-trained models for specific NLP applications, text summarization, and question-answering systems. Research and experiment with cutting-edge ML techniques and optimize model performance. Collaborate with product managers and software engineers to create end-to-end solutions that scale in production. Evaluate and improve model accuracy, scalability, and performance using appropriate metrics. Stay updated on the latest trends in NLP and machine learning to implement best practices. Required Skills and Qualifications: 3-6 years of experience in machine learning with a focus on NLP Hands-on experience with BERT and other transformer models Proficiency in working with large language models (e.g., GPT, T5, etc.) Strong programming skills in Python, with experience in ML libraries like PyTorch, Hugging Face Deep understanding of tokenization, embeddings, sequence-to-sequence models, and attention mechanisms Experience with fine-tuning models for specific use cases Familiarity with data preprocessing techniques for NLP tasks Experience with ML Serving for deploying models at scale Strong problem-solving skills and ability to work in a fast-paced environment