6+ Transformer Jobs in India

Job Description

Phonologies is seeking a Senior Data Engineer to lead data engineering efforts for developing and deploying generative AI and large language models (LLMs). The ideal candidate will excel in building data pipelines, fine-tuning models, and optimizing infrastructure to support scalable AI systems for enterprise applications.

Role & Responsibilities

• Data Pipeline Management: Design and manage pipelines for AI model training, ensuring efficient data ingestion, storage, and transformation for real-time deployment.
• LLM Fine-Tuning & Model Lifecycle: Fine-tune LLMs on domain-specific data, and oversee the model lifecycle using tools like MLFlow and Weights & Biases.
• Scalable Infrastructure: Optimize infrastructure for large-scale data processing and real-time LLM performance, leveraging containerization and orchestration in hybrid/cloud environments.
• Data Management: Ensure data quality, security, and compliance, with workflows for handling sensitive and proprietary datasets.
• Continuous Improvement & MLOps: Apply MLOps/LLMOps practices for automation, versioning, and lifecycle management, while refining tools and processes for scalability and performance.
• Collaboration: Work with data scientists, engineers, and product teams to integrate AI solutions and communicate technical capabilities to business stakeholders.

Preferred Candidate Profile

• Experience: 5+ years in data engineering, focusing on AI/ML infrastructure, LLM fine-tuning, and deployment.
• Technical Skills: Advanced proficiency in Python, SQL, and distributed data tools.
• Model Management: Hands-on experience with MLFlow, Weights & Biases, and model lifecycle management.
• AI & NLP Expertise: Familiarity with LLMs (e.g., GPT, BERT) and NLP frameworks like Hugging Face Transformers.
• Cloud & Infrastructure: Strong skills with AWS, Azure, Google Cloud, Docker, and Kubernetes.
• MLOps/LLMOps: Expertise in versioning, CI/CD, and automating AI workflows.
• Collaboration & Communication: Proven ability to work with cross-functional teams and explain technical concepts to non-technical stakeholders.
• Education: Degree in Computer Science, Data Engineering, or related field.

Perks and Benefits

• Competitive Compensation: INR 20L to 30L per year.
• Innovative Work Environment for Personal Growth: Work with cutting-edge AI and data engineering tools in a collaborative setting, for continuous learning in data engineering and AI.

Data Scientist is responsible to discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver better products. Your primary focus will be in applying Machine Learning and Generative AI techniques for data mining and statistical analysis, Text analytics using NLP/LLM and building high quality prediction systems integrated with our products. The ideal candidate should have a prior background in Generative AI, NLP (Natural Language Processing), and Computer Vision techniques. Additionally, experience in working with current state of the art Large Language Models (LLMs), and Computer Vision algorithms.

Job Responsibilities:

»    Building models using best in AI/ML technology.

»    Leveraging your expertise in Generative AI, Computer Vision, Python, Machine Learning, and Data Science to develop cutting-edge solutions for our products.

»    Integrating NLP techniques, and utilizing LLM's in our products.

»    Training/fine tuning models with new/modified training dataset.

»    Selecting features, building and optimizing classifiers using machine learning techniques.

»    Conducting data analysis, curation, preprocessing, modelling, and post-processing to drive data-driven decision-making.

»    Enhancing data collection procedures to include information that is relevant for building analytic systems

»    Working understanding of cloud platforms (AWS).

»    Collaborating with cross-functional teams to design and implement advanced AI models and algorithms.

»    Involving in R&D activities to explore the latest advancements in AI technologies, frameworks, and tools.

»    Documenting project requirements, methodologies, and outcomes for stakeholders.

Technical skills

Mandatory

»    Minimum of 5 years  of experience as Machine Learning Researcher or Data Scientist.

»    Master's degree or Ph.D. (preferable) in Computer Science, Data Science, or a related field.

»    Should have knowledge and experience in working with Deep Learning projects using CNN, Transformers, Encoder and decoder architectures.

»    Working experience with LLM's (Large Language Models) and their applications (For e.g., tuning embedding models, data curation, prompt engineering, LoRA, etc.).

»    Familiarity with LLM Agents and related frameworks.

»    Good programming skills in Python and experience with relevant libraries and frameworks (e.g., PyTorch, and TensorFlow).

»    Good applied statistics skills, such as distributions, statistical testing, regression, etc.

»    Excellent understanding of machine learning and computer vision based techniques and algorithms.

»    Strong problem-solving abilities and a proactive attitude towards learning and adopting new technologies.

»    Ability to work independently, manage multiple projects simultaneously, and collaborate effectively with diverse stakeholders.

Nice to have

»    Exposure to financial research domain

»    Experience with JIRA, Confluence

»    Understanding of scrum and Agile methodologies

»    Basic understanding of NoSQL databases, such as MongoDB, Cassandra

Experience with data visualization tools, such as Grafana, GGplot, etc.

About us:

Pi - India’s 1st SuperMoney App, is an AI-native Fintech startup building ML platforms for financial advisory and wealth management. Founded by a former Investment Banker (IIT/IIM/ CFA®) with over a decade of experience.

We are looking for Machine Learning Engineers who are passionate about developing world-class ML platforms. You will be part of the Core Founding team that lays the foundation for a Unicorn journey. You'll join a visionary, funded startup on the ground floor and get to build it up one conversation at a time.

Qualifications:

• Overall experience of 4 to 7 years in ML
• B.Tech/BE from top-tier colleges (IIT, NIT, IIIT)

Requirements:

• Applied GenAI expertise in implementing cutting-edge LLMs and diverse generative models, specializing in transformers and GPT models.
• Demonstrated proficiency across various modalities, showcasing a dynamic skill set for innovative solutions.
• Expertise in Natural Language Processing (NLP), with a comprehensive understanding of the entire stack involved in designing, training, evaluating, and deploying machine learning models, particularly large language models.
• Deep understanding of the entire stack when it comes to designing, training, evaluating, and deploying ML models. Successfully collected a new giant dataset and played a critical role in shipping a new ML product that required custom components.
• Extensive experience in designing and building intelligent agents, leveraging AI techniques to create autonomous and adaptive systems for various applications.
• Proficient in writing distributed ML infrastructure, debugging and fixing hard-to-find bugs in ML models, and owning production-grade projects from start to finish.
• Experience with Deep learning frameworks such as PyTorch, TensorFlow. , Jax, and Keras.
• Proficient in writing GPU kernels using CUDA .
• Experience with AWS SageMaker and the AWS Machine Learning suite of tools.
• Developed novel techniques for ML model measurement and mitigation.
• Proficient in Apache Kafka for seamless data streaming, Apache Spark for large-scale batch processing, and Apache Airflow for efficient orchestration.
• Demonstrated expertise in Kubernetes-based workflows, specifically Kubeflow, for scalable and portable machine learning and data processing deployments, enhancing pipeline reliability and performance.
• Experience with MongoDB, MySQL, and Vector databases.
• Experience with analytics.
• Proficient in Kubernetes, Python, Github, Huggingface, R(for Analytics)
• Experience in mentoring and growing engineers.

Additional Benefits:

Competitive compensation along with ESOPs of a path-breaking Fintech startup

Are you passionate about pushing the boundaries of Artificial Intelligence and its applications in the software development lifecycle? Are you excited about building AI models that can revolutionize how developers ship, refactor, and onboard to legacy or existing applications faster? If so, Zevo.ai has the perfect opportunity for you!

As an AI Researcher/Engineer at Zevo.ai, you will play a crucial role in developing cutting-edge AI models using CodeBERT and codexGLUE to achieve our goal of providing an AI solution that supports developers throughout the sprint cycle. You will be at the forefront of research and development, harnessing the power of Natural Language Processing (NLP) and Machine Learning (ML) to revolutionize the way software development is approached.

Responsibilities:

1. AI Model Development: Design, implement, and refine AI models utilizing CodeBERT and codexGLUE to comprehend codebases, facilitate code understanding, automate code refactoring, and enhance the developer onboarding process.
2. Research and Innovation: Stay up-to-date with the latest advancements in NLP and ML research, identifying novel techniques and methodologies that can be applied to Zevo.ai's AI solution. Conduct experiments, perform data analysis, and propose innovative approaches to enhance model performance.
3. Data Collection and Preparation: Collaborate with data engineers to identify, collect, and preprocess relevant datasets necessary for training and evaluating AI models. Ensure data quality, correctness, and proper documentation.
4. Model Evaluation and Optimization: Develop robust evaluation metrics to measure the performance of AI models accurately. Continuously optimize and fine-tune models to achieve state-of-the-art results.
5. Code Integration and Deployment: Work closely with software developers to integrate AI models seamlessly into Zevo.ai's platform. Ensure smooth deployment and monitor the performance of the deployed models.
6. Collaboration and Teamwork: Collaborate effectively with cross-functional teams, including data scientists, software engineers, and product managers, to align AI research efforts with overall company objectives.
7. Documentation: Maintain detailed and clear documentation of research findings, methodologies, and model implementations to facilitate knowledge sharing and future developments.
8. Ethics and Compliance**: Ensure compliance with ethical guidelines and legal requirements related to AI model development, data privacy, and security.

Requirements

1. Educational Background: Bachelor's/Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A strong academic record with a focus on NLP and ML is highly desirable.
2. Technical Expertise: Proficiency in NLP, Deep Learning, and experience with AI model development using frameworks like PyTorch or TensorFlow. Familiarity with CodeBERT and codexGLUE is a significant advantage.
3. Programming Skills: Strong programming skills in Python and experience working with large-scale software projects.
4. Research Experience: Proven track record of conducting research in NLP, ML, or related fields, demonstrated through publications, conference papers, or open-source contributions.
5. Problem-Solving Abilities: Ability to identify and tackle complex problems related to AI model development and software engineering.
6. Team Player: Excellent communication and interpersonal skills, with the ability to collaborate effectively in a team-oriented environment.
7. Passion for AI: Demonstrated enthusiasm for AI and its potential to transform software development practices.

If you are eager to be at the forefront of AI research, driving innovation and impacting the software development industry, join Zevo.ai's talented team of experts as an AI Researcher/Engineer. Together, we'll shape the future of the sprint cycle and revolutionize how developers approach code understanding, refactoring, and onboarding!