2+ Transformer Jobs in Pune | Transformer Job openings in Pune

About Us

We are a fast-growing startup based in Pune, India, specializing in cutting-edge Data Science and Data Engineering solutions. Our team of dedicated professionals is committed to solving complex data challenges for companies worldwide.

Our Culture We foster a vibrant startup culture that values: • Intellectual curiosity • Continuous learning • Positive work environment • Collaborative problem-solving

Role Overview

We are seeking a versatile and proactive Data Scientist to join our dynamic team. The ideal candidate will possess a blend of technical expertise in modern AI/ML technologies, strategic planning, and effective communication skills. This role demands critical thinking, applying data science and problem-solving skills to a wide variety of real-world problems, adaptability to rapidly evolving technologies, and a strong foundation in both traditional and generative AI principles.

Key Responsibilities • Deliver end-to-end data science projects by applying Machine Learning and Deep Learning fundamentals to solve complex problems • Derive actionable insights for a variety of problems, industries, and domains using statistical analysis and advanced data science techniques • Develop high-quality software solutions with Python and other programming languages. Collaborate with developers to understand and improve existing code or create new solutions • Build and deploy production-ready LLM applications using modern frameworks and best practices • Design and implement RAG (Retrieval-Augmented Generation) architectures using vector databases and embedding models • Perform prompt engineering and optimization to maximize LLM performance for specific use cases • Implement agentic AI systems and multi-agent workflows for complex automation tasks • Evaluate and benchmark LLM outputs using appropriate metrics and testing frameworks • Build sophisticated data pipelines for large-scale data processing using modern orchestration tools • Optimize database performance and create efficient SQL queries • Deploy and monitor ML models in production using MLOps practices and containerization • Practice active listening to understand project requirements and team inputs • Collaborate with clients to translate business requirements into data science solutions • Communicate complex ideas and results clearly to stakeholders through both verbal and written formats • Apply responsible AI principles and ensure ethical considerations in model development • Demonstrate punctuality and a strong sense of ownership in all tasks • Plan strategically and multitask efficiently to meet project deadlines • Employ critical thinking to break down problems and debug effectively • Take initiative and be biased towards action to drive project progress Required Skills Core Programming & ML • Strong Python programming skills with hands-on project experience • Expertise in Machine Learning and Deep Learning algorithms (Random Forests, GBMs, Neural Networks, CNNs, RNNs, Transformers, Ensemble methods) • Proficiency in TensorFlow or PyTorch, along with scikit-learn and pandas • Familiarity with modern ML techniques: Transfer Learning, Few-shot Learning, Self-supervised Learning • Experience with NLP, Computer Vision, or Time Series Analysis Generative AI & LLMs • Hands-on experience with LLM providers (OpenAI, Anthropic Claude, Google Gemini, or open-source models) • Proficiency with GenAI orchestration frameworks (LangChain, LangGraph, LlamaIndex, or DSPy) • Experience building RAG applications with vector databases (Pinecone, Weaviate, Chroma, FAISS) • Strong prompt engineering skills and understanding of prompt optimization techniques • Knowledge of fine-tuning techniques (LoRA, QLoRA) and when to apply them • Understanding of LLM evaluation metrics and benchmarking methodologies • Familiarity with agentic AI architectures and multi-agent systems MLOps & Deployment • Experience with MLOps practices and tools (MLflow, Kubeflow, Weights & Biases) • Proficiency with containerization using Docker and orchestration with Kubernetes • Experience with cloud platforms (AWS, Azure, or GCP) for ML model deployment and monitoring • Understanding of CI/CD pipelines for ML applications • Knowledge of model serving frameworks and API development (FastAPI, Flask, or Django) Data Engineering & Databases • Solid understanding of SQL, including advanced concepts like windowing functions and query optimization • Experience with data pipeline orchestration tools (Airflow, Prefect, or similar) • Familiarity with both SQL and NoSQL databases Soft Skills & Professional Attributes • Strong critical thinking and problem-solving skills • Excellent written and verbal communication abilities • Demonstrated ability to work well in a team and independently • High degree of flexibility and adaptability to rapidly evolving technologies • Understanding of AI safety principles and responsible AI practices

Nice-to-Have • Experience with big data technologies (Spark, Hadoop, Databricks) • Familiarity with BI tools and dashboard creation (Tableau, Power BI, Looker) • Knowledge of graph databases and knowledge graph construction • Experience with real-time streaming data processing • Active participation in data science competitions (Kaggle, DrivenData) • Contributions to open-source AI/ML projects or technical blog • Experience with multimodal AI models (vision-language models, audio processing) • Published research papers or conference presentations

Qualifications • Data Scientist I: 0-2 years of hands-on experience in Data Science projects • Data Scientist II: 2-5 years of hands-on experience in Data Science projects • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related technical field • Demonstrated commitment to continuous learning through courses, certifications, or self-study (especially in GenAI and modern ML techniques)

What We Offer • Competitive salary commensurate with experience • Opportunity to work on diverse, cutting-edge AI/ML projects • Collaborative and innovation-driven work environment • Rapid growth and continuous learning opportunities • Exposure to latest AI technologies and industry best practices

Link for application -  https://forms.gle/9GENVfPeXdtgi7Zj7

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.