8 Qlora Jobs

Senior AI Engineer ???? Mumbai | Hybrid About Quantanite Were a global CX and digital solutions partner that blends cutting-edge AI with the human touch. Headquartered in London and operating across 4 continents, our 2,000+ people help some of the worlds fastest-growing brands scale smarter, work faster, and deliver better serviceevery time. Were not your typical outsourcing company. At Quantanite, great service is built on two things: smart tech and smarter people. From proprietary AI platforms like MBIUS to our collaborative, people-first culture, we equip our teams with the freedom and tools to build game-changing solutions. If youre looking for a place where your AI engineering skills can shape real enterprise impact (not just POCs), youll feel at home here. The Role As a Senior AI Engineer , youll own the full lifecycle of AI solutionsfrom design to production. Youll be hands-on with multi-agent workflows, advanced knowledge retrieval, and LLM optimization to solve enterprise-scale problems. Expect to lead projects such as AI Copilots, Enterprise Search Systems, Summarization Engines, and Intelligent Automation Tools building robust, scalable solutions that move beyond prototypes into production. Youll also play a key role in mentoring junior engineers, setting engineering standards, and collaborating cross-functionally to ensure delivery at scale. What Youll Do Build and deploy agentic systems and multi-agent workflows using LangChain, LlamaIndex, OpenAI SDK (and beyond). Design RAG pipelines with vector DBs like FAISS, Pinecone, Weaviate, or Qdrant. Fine-tune and optimize LLMs (GPT-4, Claude, LLaMA, Mistral, Gemini) with LoRA/QLoRA, quantization, and other techniques. Implement guardrails, safe API usage, and PII protection for secure deployments. Monitor/evaluate agent performance with LangSmith, AgentOps , and similar tools. Ship real-world enterprise AI use casesCopilots, orchestration engines, intelligent search, and more. Mentor and review the work of junior AI engineers, spreading best practices. Work with product, data, and DevOps teams to bring AI solutions into production at scale. What Youll Bring Solid grounding in LLMs and GenAI (fine-tuning, prompt engineering, practical deployment). Proven track record with RAG pipelines and vector databases. Hands-on with agent frameworks (LangChain, LlamaIndex, etc.) and orchestration. Experience deploying/scaling models on clouds (AWS, Azure, HuggingFace). Strong coding ability in Python or similar. Familiarity with LLM Ops : monitoring, evaluation, cost optimisation. Delivered enterprise-grade AI solutions (not just demos). Experience mentoring engineers and building technical excellence in a team. Bonus: contributed to open-source LLM projects or worked on autonomous agent use cases (research copilots, orchestration systems). Qualifications B.Tech (required). 4.57 years of relevant experience. Strong knowledge of GenAI, agentic systems, and multi-agent architectures. Attributes: clear communicator, strong leader, highly tech-savvy. Preferred: exposure to BPO/KPO environments or systems experience in enterprise AI/agentic tools. Why Quantanite ???? Hybrid work model. ???? Ongoing training, mentorship & career growth. ???? Inclusive, people-first culture. ???? Health insurance & provident fund. Quantanite is an equal opportunity employer. We celebrate diversity and are committed to building an inclusive environment for all. ???? Ready to push agentic AI beyond theory into enterprise-scale impact Lets build the future together. Apply today to discover how we can build better, together. Show more Show less

You are a highly skilled and innovative Senior Python Developer specializing in Generative AI and MLOps tools such as Argo Workflows and Kubernetes. Your role involves designing and deploying scalable GenAI applications, constructing robust pipelines, and integrating AI models into production environments. As a Python Developer, you will be responsible for designing, developing, and fine-tuning generative models like GPT, LLAMA, Mistral, FLAN, and T5. You will also build and optimize Retrieval-Augmented Generation (RAG) pipelines, implement model evaluation frameworks, and ensure responsible AI deployment. Your expertise in writing efficient, reusable, and testable Python code for AI/ML applications will be crucial in collaborating with data scientists to integrate models into scalable systems and maintaining high-performance Python applications for real-time inference. In the realm of MLOps and Infrastructure, you will develop and manage workflows using Argo Workflows for model training and deployment. Additionally, you will containerize applications using Docker, orchestrate deployments with Kubernetes, and monitor and optimize GPU usage on cloud platforms like AWS, Azure, and Databricks. Collaboration and Delivery are key aspects of your role, as you will work cross-functionally with engineering, product, and data teams to deliver AI solutions. You will interpret research papers and model architecture diagrams to guide implementation, ensuring timely delivery of AI projects with high reliability and scalability. To excel in this role, you should hold a Bachelors or Masters degree in Computer Science, AI/ML, or a related field, with at least 4+ years of experience in Python development and data science. Hands-on experience with LLM APIs, Hugging Face, transformer models, and proficiency in deep learning frameworks like PyTorch, TensorFlow, and Keras are essential. A strong understanding of Argo Workflows, Kubernetes, containerization, cloud platforms, GPU optimization, NLP tools, SQL, and Spark will be advantageous. Preferred experience includes fine-tuning models using LoRA, QLoRA, and quantization techniques, building multi-agent systems, multimodal applications, and knowledge of AI safety, ethics, and compliance. Join Tredence, a leading analytics partner dedicated to transforming data into actionable insights for Fortune 500 clients. With a global presence and a mission to drive unparalleled business value through advanced AI and data science, we welcome you to embark on this innovative journey with us.,

As an experienced Python programmer, you will be responsible for developing GenAI applications and automation tools using your deep expertise in Python. Your role will involve the productionization of GenAI applications beyond Proof of Concepts (PoCs) by utilizing scale frameworks and tools such as Pylint and Pyrit. In addition to Python programming, you should be proficient in working with LLM Frameworks, including Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. Your expertise in these frameworks will be essential for enhancing GenAI applications. Moreover, you will leverage your extensive experience with cloud platforms such as Azure, GCP, and AWS to deploy and manage GenAI applications effectively. Your knowledge of at least two of these cloud platforms will be crucial for the success of the projects. You should also possess mastery of fine-tuning techniques like PEFT, QLoRA, LoRA, and other methods to optimize the performance of GenAI applications. Your understanding of these techniques will contribute to the overall efficiency of the applications. Furthermore, your strong knowledge of LLMOps practices for model deployment, monitoring, and management will ensure the seamless operation of GenAI applications. Your expertise in LLMOps will be vital for the successful deployment and maintenance of models. As part of your role, you will be required to implement responsible AI practices and ensure compliance with regulations to uphold ethical standards. Your proficiency in Responsible AI will be essential for developing applications that align with ethical guidelines. Additionally, you should have experience in API integration using protocols such as REST, SOAP, and others. Your familiarity with API integration will enable seamless communication between different systems and enhance the functionality of GenAI applications.,

Role: Senior AI/ML Engineer Function: Machine Learning / AI Engineering Industry: Fintech, SaaS, Artificial Intelligence About Company The client is an early-stage, venture-backed fintech using AI to simplify cash-flow analytics for high-volume B2C businesses. Its platform pairs natural-language queries with machine learning to deliver real-time insights and friction-free reconciliation. You join a small, fast-moving team that prizes ownership, experimentation, and transparent collaboration. The mission is clear: give operators instant, accurate financial visibility so they can scale with confidence. Position Overview You lead the end-to-end AI charter that powers financial automation, intelligent reconciliation, and anomaly detection. You shape the GenAI roadmap, productionize cutting-edge ML systems, and build a world-class teamall while delivering reliable, compliant, and low-latency solutions for transactional finance. Role & Responsibilities Define the AI and GenAI vision for reconciliation, document understanding, financial classification, and payment behavior intelligence. Translate product problems into scalable ML systems and GenAI workflows. Research, experiment, and productionize LLM-based pipelines tailored to enterprise financial operations. Deploy and maintain ML and LLM pipelines in production, including observability, retries, retraining, and versioning. Implement feedback loops that continuously learn from user actions and corrections. Optimize performance and latency of GenAI systems in high-throughput transactional environments. Ensure data privacy, regulatory compliance, and explainability of AI outputs in financial contexts. Lead, hire, mentor, and grow a team of ML and GenAI engineers. Collaborate with product managers, backend engineers, and data engineers to ship AI-powered features. Evangelize responsible AI practices and an experimentation culture across the organization. Must have Criteria 5+ years in AI/ML with at least 12 years hands-on with LLMs and GenAI. Deep knowledge of ML algorithms, NLP, transformers, vector search, embeddings, classification, and unsupervised learning. Proven track record building and deploying GenAI applications using OpenAI APIs, HuggingFace, LangChain, or LlamaIndex. Strong coding skills in Python and experience with PyTorch or TensorFlow, scikit-learn, pandas, and MLOps tools such as MLflow or Airflow. Hands-on experience fine-tuning LLMs (LoRA, QLoRA, PEFT) and crafting prompts for deterministic outputs. Expertise with OCR/NLP tools for semi-structured document extraction and parsing. Ability to work with unstructured, noisy financial data at scale. End-to-end ownership of ML systems from research through deployment and monitoring. Nice to Have Familiarity with open-source LLMs like Mistral, Claude, LLaMA, or Zephyr. Experience with chunking strategies, prompt templates, and hybrid search in RAG systems. Background in enterprise SaaS or fintech domains such as banking, reconciliation, ERP, or accounting. Knowledge of graph-based ML or probabilistic models for complex transaction flows. Past experience building AI systems in an early-stage startup or as a founding team member. Fintech domain expertise. What We Offer Foundational role where you define how AI evolves at the company. High impact on real-world financial decisions requiring accuracy and auditability. Ownership of deep ML and cutting-edge GenAI problems. Product-first, collaborative culture that values high agency and technical depth. Show more Show less

You are an experienced Lead Data Scientist with a minimum of 8 years of professional experience, including at least 6 years in a data science role. Your expertise lies in statistical modeling, machine learning, deep learning, and GenAI. Proficiency in Python is a must, along with hands-on experience in optimizing code for performance. You excel in data preprocessing, feature engineering, data visualization, hyperparameter tuning, and have a solid understanding of database concepts, especially while working with large datasets. You have experience deploying and scaling machine learning models in a production environment, along with familiarity with machine learning operations (MLOps) and related tools. Your knowledge extends to Generative AI concepts and LLM finetuning, supported by excellent communication and collaboration skills. Your responsibilities as a Lead Data Scientist include guiding and mentoring a high-performance team on the latest technology landscape, patterns, and design standards. You provide strategic direction and technical leadership for AI initiatives, leading the design and architecture of complex AI systems. Your role involves developing and deploying machine learning/deep learning models to address key business challenges, applying various techniques in statistical modeling, data preprocessing, feature engineering, and more. You are proficient in areas such as computer vision, predictive analytics, natural language processing, time series analysis, and recommendation systems. Furthermore, you design and optimize data pipelines for model training and deployment, utilizing model serving frameworks and APIs for integration with other systems. Your qualifications include a Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Your primary skills encompass Python, Data Science concepts, Pandas, NumPy, Matplotlib, Artificial Intelligence, Statistical Modeling, Machine Learning, Natural Language Processing (NLP), Deep Learning, Model Serving Frameworks, MLOps, Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems, Generative AI, and proficiency in Cloud Computing Platforms. Your secondary skills involve expertise in designing scalable and efficient model architectures, the ability to assess and forecast financial requirements of data science projects, and strong communication skills for conveying technical concepts to stakeholders. As a Lead Data Scientist, you stay updated with the latest advancements in data science and machine learning, particularly in generative AI, to evaluate their potential applications and serve as a primary point of contact for client managers.,

As an AI Specialist at our company based in Hyderabad, you will be responsible for training and fine-tuning LLMs such as LLaMA and Mistral to cater to company-specific use cases. You will play a vital role in customizing and optimizing model performance for seamless production deployment. Collaboration with internal teams for model integration and data pipelines will be a key aspect of your role. It is imperative that you stay abreast of the latest advancements in GenAI and LLM techniques to contribute effectively. To excel in this role, you must possess hands-on experience with LLMs and fine-tuning techniques. Your expertise in the specifics of vector database indexing will be highly beneficial. We are looking for someone with a robust background in advanced AI/ML techniques and database indexing, particularly in the context of production projects. Familiarity with technologies such as LoRA, QLoRA, RAG, and PEFT is desirable. Additionally, your knowledge of model evaluation, optimization, and GPU training will be crucial for success in this position.,

Are you obsessed with pushing the boundaries of Generative AI? Have you fine tuned LLaMA models, dived into LoRA or even full-scale fine tuning? Then this opportunity is tailor-made for you ! We are on the hunt for AI /ML Engineers/ Research Engineers /ML Developers with Strong experience in LLM Fine tuning and python to join our AI innovation team. Location : Siruseri, Chennai, Experience : 2 to 10 Years Notice Period : Immediate Joiners to 30 Days Role & responsibilities : Fine-tune LLaMA models on domain-specific data (e.g., finance, healthcare, telecom, legal, etc.) Curate, clean, and pre-process datasets for supervised and unsupervised fine-tuning. Implement low-rank adaptation (LoRA), PEFT, QLoRA, or full fine-tuning as per need. Optimize model training performance using tools/libraries. Evaluate fine-tuned models using appropriate metrics. Deploy and integrate models with APIs, RAG pipelines, or inference servers. Use tools like Weights & Biases, LangSmith, or TensorBoard for training monitoring and logging. Conduct safety audits and hallucination checks post-fine-tuning. Familiarity with open-source LLMs beyond LLaMA (Mistral, Falcon, Mixtral, etc.). Hands-on with orchestration tools like LangChain, LangGraph, CrewAI, or Flowise. Knowledge of tokenizers, embeddings, and prompt templates. Experience with LLaMA (preferably LLaMA 2 / LLaMA 3) and Hugging Face ecosystem. Proficiency in Python, PyTorch, and model training workflows. what are we looking for ? Deep expertise in Fine tuning in LLama, LoRA, QLoRA & strong command of Python & ML Libraries Why join us? Work with Top tier AI minds Get access to high performance infra for model training Drive innovation with real world applications Be part of a growing AI team building next -gen tools. Nonstop learning and innovation Competitive salary + growth opportunities Ready to build the future with LLM'S? Apply now and shape the future of AI ! Tag your resume to Latha.s@excelacom.in / +91 7667620910 and GitHub with your latest fine- tuning experiments . Lets build the future together - one fine- tuned model at a time.

Hinduja Global Solutions (HGS) is a global company specializing in business process management (BPM) and digital customer experience (CX) solutions. HGS offers a range of services including contact center solutions, back-office processing, and integrated digital platforms. They are part of the Hinduja Group, a large multinational conglomerate. With over 20,000 employees across 34 delivery centers in 8 countries, HGS offers a spectrum of technology, digital marketing, and outsourcing solutions tailored to specific industry verticals. What we are looking for: Core Skills & Knowledge Programming: Expert Python; deep use of Pandas, NumPy, Scikit-learn, PyTorch/Lightning; strong OO and functional patterns. Large Language Models: Fine-tuning (LoRA, QLoRA, PEFT), prompt engineering, evaluation (BLEU, BERTScore, hallucination metrics). Machine Learning: Classical algorithms (tree-based, linear, ensemble, time-series), hyper-parameter search (Optuna, Ray Tune), model explainability (SHAP, Captum). Statistical Methods: Experimental design, p-value and power analysis, Bayesian A/B testing, causal inference. Vector Search & RAG: Embedding generation, similarity search tuning (HNSW, IVF-PQ), chunking strategies, knowledge-base hygiene. DevOps & Tooling: Git, Docker, Conda/Poetry, make/Task, notebook versioning, automated linting & unit tests (pytest). Cloud & Data Platforms: Familiarity with AWS (SageMaker, Bedrock) or Azure (ML, OpenAI) plus modern data warehouses (Snowflake, Redshift, BigQuery) and lake formats (Parquet, Delta). Why this role matters We deliver data-driven and GenAI-powered products that move business KPIs, not just models. Youll transform raw data and cutting-edge research (LLMs, causal inference, RAG pipelines) into production-grade capabilities that customers use every day. Key Responsibilities Responsibility Model development & experimentation – Build and validate supervised/unsupervised models (classification, regression, clustering) and LLM fine-tuning pipelines; design statistically rigorous experiments (A/B, multivariate, uplift). This also includes RAG applications, and tune RAG workflows with vector databases (pgvector, Milvus) and embeddings (OpenAI, Hugging Face). Optimize retrieval recall, latency, and hallucination rates. Causal & statistical analysis – Apply quasi-experimental methods (DID, propensity scoring, synthetic controls) and hypothesis tests to uncover drivers of business outcomes. Operationalization & MLOps – Package models as reproducible artifacts (MLflow, TorchScript, BentoML), write CI/CD tests, and partner with MLOps engineers on scalable deployment and monitoring. Data wrangling & feature engineering – Build robust ETL/ELT pipelines in Python (Pandas, Polars, SQL) and orchestrate workflows (Airflow, Dagster). Collaboration & knowledge sharing – Translate findings to non-technical stakeholders, contribute to shared notebooks, mentor junior analysts, and document best practices. Nice-to-Have / Stretch Skills Graph data science (Neo4j, Graph-SAGE) Streaming ML on Apache Kafka / Flink LangChain / LlamaIndex orchestration Real-time feature stores (Feast, Tecton) Domain knowledge in finance, healthcare, or supply chain Experience & Education 6-10 years of overall IT experience with over 5 years of relevant experience building and shipping ML models or GenAI services in production. Proven track record of improving a business metric (conversion, churn, NPS, cost) through data science. Bachelor’s or Master’s in Computer Science, Statistics, Mathematics, or related field (or equivalent hands-on experience). Working at HGS: At TekLink our employees get an open and collaborative environment and gain experience working for customers in various industries while solving complex business problems. They get support to learn new technologies as well as to enhance existing skills to further their career growth. We offer: Very competitive remuneration Excellent Benefits including – Hot Skills allowance, Shift allowance, Health, accidental and Life coverage. Excellent performance based annual increments. Fast paced growth opportunities International work experience Opportunity to participate in various sports and CSR activities.