Data Scientist

About Nexora Group

Nexora Group is a technology and innovation-driven organization dedicated to building intelligent solutions that leverage Artificial Intelligence, Machine Learning, Data Analytics, and emerging technologies. We are committed to fostering talent by providing aspiring professionals with practical exposure, mentorship, and opportunities to work on real-world projects.

Internship Overview

Nexora Group is looking for enthusiastic and driven AI/ML Interns to join our team. This internship is ideal for students and recent graduates who are passionate about Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI. Interns will gain hands-on experience working on real-world AI projects, developing intelligent models, and solving complex business challenges using data-driven approaches.

Key Responsibilities

• Assist in developing, training, and evaluating Machine Learning models.
• Collect, clean, and preprocess datasets for AI/ML applications.
• Conduct exploratory data analysis and feature engineering.
• Work on Deep Learning, Natural Language Processing (NLP), and Computer Vision projects.
• Research and implement AI algorithms and emerging technologies.
• Support the development of Generative AI and Large Language Model (LLM)-based solutions.
• Optimize model performance and evaluate results using industry-standard metrics.
• Document project workflows, findings, and technical reports.
• Collaborate with cross-functional teams to develop innovative AI solutions.

Required Skills

• Basic understanding of Machine Learning and Artificial Intelligence concepts.
• Knowledge of Python programming.
• Familiarity with libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, or Keras.
• Understanding of data structures, algorithms, and statistics.
• Basic knowledge of Deep Learning, NLP, or Computer Vision concepts.
• Strong analytical and problem-solving skills.
• Good communication and teamwork abilities.
• Willingness to learn and adapt to new technologies.

Preferred Qualifications

• Experience with AI/ML projects, hackathons, or research work.
• Knowledge of Generative AI, Prompt Engineering, and LLMs.
• Familiarity with cloud platforms and AI deployment tools.
• Certifications in AI, Machine Learning, or Data Science are a plus.
• GitHub projects or portfolio showcasing AI/ML work.

Eligibility

• Undergraduate or postgraduate students pursuing Computer Science, Artificial Intelligence, Machine Learning, Data Science, Information Technology, or related fields.
• Recent graduates seeking practical industry experience.
• Candidates with a strong interest in AI innovation and research.

What You'll Gain

• Hands-on experience with real-world AI and Machine Learning projects.
• Mentorship from experienced AI professionals.
• Exposure to cutting-edge AI tools, frameworks, and technologies.
• Internship Completion Certificate.
• Letter of Recommendation based on performance.
• Opportunity for a Pre-Placement Offer (PPO) for outstanding performers.
• Professional networking and career development opportunities.

Job Summary/ Job Opportunity:

This is an excellent opportunity for an ideal candidate with a high level of technical proficiency and meeting the below mentioned criteria -- • Strong experience in Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs). • Hands-on experience building and deploying production-grade solutions using Azure OpenAI, OpenAI, LangChain, LangGraph, Semantic Kernel, LlamaIndex, and Agentic AI frameworks. • Strong expertise in Python, API development, microservices, and cloud-native architectures. • Experience designing and implementing RAG solutions, vector databases, embeddings, knowledge retrieval systems, and AI copilots. • Experience with Azure cloud services, MLOps, CI/CD pipelines, monitoring, and model lifecycle management. • Strong understanding of AI governance, responsible AI, security, compliance, and model evaluation frameworks. • Ability to lead technical discussions, provide architectural recommendations, mentor team members, and interact with business stakeholde

Key Objectives and Major Responsibilities:

• Design, develop, and implement scalable AI/ML and Generative AI solutions for enterprise applications. • Lead development of intelligent applications leveraging LLMs, RAG pipelines, AI agents, and document intelligence solutions. • Collaborate with business stakeholders, architects, and product teams to translate business requirements into technical solutions. • Design and optimize data pipelines, vector search solutions, embeddings, and retrieval mechanisms. • Build and maintain REST APIs, microservices, and cloud-native AI applications. • Ensure best practices in coding standards, performance optimization, security, scalability, and maintainability. • Drive AI solution deployment using MLOps practices, CI/CD pipelines, monitoring, and observability frameworks. • Perform code reviews, mentor junior developers, and contribute to capability building within the team

Key Capabilities and Competencies:

Knowledge, Skills, Qualification and Experience

• Degree in B.Tech/M.Tech (Computer Science/IT/Data Science) or related discipline preferred, with 3–4 years of relevant experience in AI/ML, GenAI and total 5-7 years of experience. • Proficiency in Python and hands-on experience with ML libraries (scikit-learn, TensorFlow, PyTorch) and GenAI frameworks/tools. • Strong understanding of machine learning, deep learning, LLMs, prompt engineering, and techniques like RAG and fine-tuning. • Experience with data processing, embeddings, vector databases, APIs, and building scalable AI driven applications. • Good communication skills, ability to work on multiple projects, and eagerness to learn and adapt to evolving AI technologies. 

Job Description:

We are seeking a versatile and highly skilled Lead AI/ML Engineer with deep expertise in Generative AI (GenAI) and Large Language Models (LLMs). This role requires a leader who can take full ownership of the

AI lifecycle—from initial architectural design to final production execution. You will lead the development of scalable AI-powered applications, demonstrating exceptional execution skills and the ability to deliver high-performance results under pressure in demanding production environments.

Machine Learning & LLM Capability:

 End-to-End ML Engineering: Build and manage comprehensive ML pipelines, including data ingestion, preprocessing, training, and evaluation using frameworks like PyTorch, TensorFlow, and Scikit-learn.  Advanced LLM Systems: Design and implement sophisticated LLM-based applications such as autonomous agents, chatbots, and complex automation tools.

 Generative AI Specialization: Architect and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Pinecone, or Weaviate.

 Model Optimization: Fine-tune open-source and proprietary models (e.g., LLaMA, GPT) using advanced techniques like LoRA, QLoRA, or instruction tuning.

 Agentic Frameworks: Develop complex agentic workflows utilizing frameworks such as LangChain or LlamaIndex.

 Prompt Engineering: Implement expert-level prompt engineering, tool/function calling, and structured output generation.

 Project Ownership & Execution

 Full Lifecycle Ownership: Take complete accountability for the full ML and GenAI lifecycle, spanning data processing, model development, monitoring, and optimization.

 Architectural Leadership: Drive strategic architectural decisions for AI platforms, ensuring they are modular, scalable, and maintainable.

 Execution Excellence: Write clean, high-performance Python code following strict OOP principles and manage CI/CD pipelines for seamless project execution.

 Leadership & Mentoring: Act as a key technical leader, managing stakeholders and mentoring team members to ensure all project milestones are met with quality.

 System Integrity: Manage model and prompt versioning, experiment tracking, and comprehensive documentation for all pipelines and workflows.

 Performance Under Pressure

 Production Reliability: Ensure all AI systems maintain extreme scalability and performance under heavy production workloads, including both batch and real-time processing.

 High-Pressure Optimization: Rapidly optimize inference latency and system costs for ML and LLM systems to meet urgent business and technical requirements.

 Proactive Problem Solving: Apply strong analytical thinking to address complex challenges such as system drift, hallucinations, and latency in fast-paced environments.

 Robust Guardrails: Implement and manage strict evaluation frameworks and feedback loops to maintain system quality under stress.

Qualifications:

 Bachelor’s or Master’s degree in Computer Science, AI, ML, or a related field.

 Proven expertise in Python, system design, and scalable AI/ML architecture.

 Deep knowledge of NLP, Computer Vision, and Deep Learning models.

 Hands-on experience with Docker, Kubernetes, MLOps, and major cloud platforms (AWS, GCP, or Azure).

AI/ML Engineer AI Operating System for Capital Markets Location Bangalore/Chennai Experience 5+ years Function Artificial Intelligence / Machine Learning Employment Type About Transient.AI Full-time Transient.AI is building a next-generation AI Operating System for capital markets — a unified intelligence layer that connects research, trading, compliance, and sales functions at banks and hedge funds. Today, these teams largely operate on disconnected legacy systems, forcing manual, expensive workarounds. Transient.AI replaces that fragmentation with a single AI-native layer built for institutional-grade compliance, security, and auditability. The company already has live products in market, including Caddie.AI (a research automation tool that cuts hedge fund research time significantly), ClarityRIA (helping sales teams identify the right investors in seconds), and CapFlo.AI (automated parsing of complex derivatives contracts). Founded by former traders and technologists from Goldman Sachs, Credit Suisse, UBS, and McKinsey, Transient.AI is headquartered in New York, with teams in Miami, Singapore, and India. The company has raised Series A funding and is scaling its engineering and product organization globally. Role Overview Transient.AI is hiring an experienced AI/ML Engineer to join its India engineering team in Bangalore/Chennai. This is a hands-on, build-from-scratch role — you'll be designing and shipping the core machine learning systems that power the company's flagship products, working closely with founders and senior engineers rather than inheriting existing infrastructure. Key Responsibilities • Design, build, and deploy machine learning and AI models that power Transient.AI's core products (research automation, document intelligence, investor matching, and workflow orchestration). • Workonapplied NLP/LLMsystems, including retrieval-augmented generation, structured extraction from unstructured financial documents, and model evaluation pipelines. • Partner closely with product and founding engineers to translate capital markets workflows into scalable AI systems. • Ownmodelperformance, reliability, and cost — from experimentation through production deployment. • Build and maintain data pipelines, feature stores, and evaluation frameworks to support rapid iteration. • Ensuresystems meet the compliance, auditability, and security standards required in regulated financial environments. What We're Looking For • 5+years ofexperience building and deploying machine learning or AI systems in production.• Strong hands-on experience with Python and modern ML/AI frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, or equivalent). • Experience with LLMs — fine-tuning, prompt engineering, RAG architectures, or agentic systems — is highly valued. • Solid grounding in data structures, distributed systems, and MLOps practices (model serving, monitoring, versioning). • Prior experience at a strong product company, high-growth startup, or a top-tier engineering background • Comfort operating in an early-stage, high-ownership environment with limited process and high ambiguity. • Exposure to fintech, capital markets, or other regulated industries is a plus, though not mandatory. WhyJoin Transient.AI • Build core AI systems from the ground up — not maintain legacy code. • Workdirectly with founders who have deep, first-hand Wall Street experience (Goldman Sachs, Credit Suisse, UBS, McKinsey). • JoinaSeries A-funded company solving a real, expensive problem for institutional finance. • Bepart ofasmall, global team with outsized ownership and impact. .

About NonStop io Technologies

NonStop io Technologies is a value-driven company with a strong focus on process-oriented software engineering. We specialize in Product Development and have a decade's worth of experience in building web and mobile applications across various domains. NonStop io Technologies follows core principles that guide its operations and believes in staying invested in a product's vision for the long term. We are a small but proud group of individuals who believe in the 'givers gain' philosophy and strive to provide value in order to seek value. We are committed to and specialize in building cutting-edge technology products and serving as trusted technology partners for startups and enterprises. We pride ourselves on fostering innovation, learning, and community engagement. Join us to work on impactful projects in a collaborative and vibrant environment.

Brief Description:

We're seeking an AI/ML Engineer to join our team. As AI/ML Engineer, you will be responsible for designing, developing, and implementing artificial intelligence (AI) and machine learning (ML) solutions to solve real-world business problems. You will work closely with engineering teams, including software engineers, domain experts, and product managers, to deploy and integrate Applied AI/ML solutions into the products that are being built at NonStop io. Your role will involve researching cutting-edge algorithms and data processing techniques, and implementing scalable solutions to drive innovation and improve the overall user experience.

Responsibilities

● Applied AI/ML engineering; Building engineering solutions on top of the AI/ML tooling available in the industry today. Eg: Engineering APIs around OpenAI

● AI/ML Model Development: Design, develop, and implement machine learning models and algorithms that address specific business challenges, such as natural language processing, computer vision, recommendation systems, anomaly detection, etc.

● Data Preprocessing and Feature Engineering: Cleanse, preprocess, and transform raw data into suitable formats for training and testing AI/ML models. Perform feature engineering to extract relevant features from the data

● Model Training and Evaluation: Train and validate AI/ML models using diverse datasets to achieve optimal performance. Employ appropriate evaluation metrics to assess model accuracy, precision, recall, and other relevant metrics

● Data Visualization: Create clear and insightful data visualizations to aid in understanding data patterns, model behaviour, and performance metrics

● Deployment and Integration: Collaborate with software engineers and DevOps teams to deploy AI/ML models into production environments and integrate them into various applications and systems

● Data Security and Privacy: Ensure compliance with data privacy regulations and implement security measures to protect sensitive information used in AI/ML processes

● Continuous Learning: Stay updated with the latest advancements in AI/ML research, tools, and technologies, and apply them to improve existing models and develop novel solutions

● Documentation: Maintain detailed documentation of the AI/ML development process, including code, models, algorithms, and methodologies for easy understanding and future reference.

Qualifications & Skills

● Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, or a related field. Advanced degrees or certifications in AI/ML are a plus

● Proven experience as an AI/ML Engineer, Data Scientist, or related role, ideally with a strong portfolio of AI/ML projects

● Proficiency in programming languages commonly used for AI/ML. Preferably Python

● Familiarity with popular AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, etc.

● Familiarity with popular AI/ML Models such as GPT3, GPT4, Llama2, BERT etc.

● Strong understanding of machine learning algorithms, statistics, and data structures

● Experience with data preprocessing, data wrangling, and feature engineering

● Knowledge of deep learning architectures, neural networks, and transfer learning

● Familiarity with cloud platforms and services (e.g., AWS, Azure, Google Cloud) for scalable AI/ML deployment

● Solid understanding of software engineering principles and best practices for writing maintainable and scalable code

● Excellent analytical and problem-solving skills, with the ability to think critically and propose innovative solutions

● Effective communication skills to collaborate with cross-functional teams and present complex technical concepts to non-technical stakeholders

About the Internship

Nexora Group is looking for passionate and innovative students interested in Artificial Intelligence (AI) and Machine Learning (ML). This internship offers an opportunity to work on real-world AI projects, explore machine learning techniques, and gain hands-on experience with emerging technologies that are transforming industries worldwide.

Interns will collaborate with mentors, work on practical assignments, and develop industry-relevant skills in AI, ML, data-driven decision-making, and intelligent systems.

Key Responsibilities

• Assist in developing and testing Machine Learning models.
• Work on AI-based applications and automation projects.
• Analyze datasets and prepare data for model training.
• Research emerging AI and Machine Learning technologies.
• Evaluate model performance and improve accuracy.
• Create reports and documentation for assigned projects.
• Participate in project discussions, training sessions, and team meetings.
• Support the development of innovative AI-driven solutions.

Required Skills

• Basic knowledge of Python programming.
• Understanding of Artificial Intelligence and Machine Learning concepts.
• Familiarity with data analysis and statistics.
• Knowledge of Machine Learning libraries such as Scikit-learn, TensorFlow, or PyTorch is a plus.
• Strong analytical and problem-solving skills.
• Ability to learn new technologies quickly.
• Good communication and teamwork skills.

Eligibility

• B.Tech, M.Tech, BCA, MCA, B.Sc., M.Sc., or related disciplines.
• Students pursuing Computer Science, Artificial Intelligence, Data Science, Information Technology, Mathematics, or related fields.
• Freshers and recent graduates are encouraged to apply.

What You Will Learn

✅ Artificial Intelligence Fundamentals

✅ Machine Learning Algorithms

✅ Data Preprocessing & Model Training

✅ Generative AI Concepts

✅ Predictive Analytics

✅ AI Project Development

✅ Industry-Oriented Problem Solving

Benefits

✅ Internship Completion Certificate

✅ Letter of Recommendation (Performance-Based)

✅ Hands-on AI & ML Project Experience

✅ Professional Mentorship & Guidance

✅ Resume & LinkedIn Profile Enhancement

✅ Portfolio Development Support

✅ Exposure to Real-World AI Applications

• We are looking for experienced AI/ML Architects to join our AI Engineering service line. In this role, you will anchor the technical delivery of enterprise AI/Agentic AI projects post deal-closure. You will take over from solution architects and lead the design, build, deployment, and optimization of AI/ML systems — ensuring production-grade quality, scalability, and compliance. 
• You will interface with cross-functional teams, manage engineering complexity, and ensure value realization for customers across industries such as BFSI, HLS, Manufacturing, CMT, Retail, and Energy. 

Key Responsibilities

Architecture & Technical Leadership

Hands-on Engineering & Problem Solving

Required Qualifications

Education : B.Tech/M.Tech or equivalent in Computer Science, Data Science, or a related field.

Experience

● 10+ years in software architecture or engineering with 5+ years in applied AI/ML

system delivery.

● Experience in productionizing AI/ML models and building full-stack AI applications in

enterprise settings.

● Strong Python development skills; proficiency in ML/AI frameworks (PyTorch,

TensorFlow, Scikit-learn).

● Strong understanding of LLMs, RAG pipelines, vector databases (Weaviate, Qdrant,

Pinecone).

● Experience with MLOps/LLMOps tools: MLflow, Argo, KServe, Feast, Kubeflow.

● Proficiency in data pipeline engineering using Spark, Airflow, or DataFlow.

● Exposure to agent orchestration frameworks: LangChain, LangGraph, AutoGen,

CrewAI is a big plus.

● Cloud & Infrastructure

● Hands-on experience with GCP (Vertex AI, BigQuery, Document AI, AI Gateway)

and/or Azure (Azure ML, OpenAI, Synapse).

● Expertise in containerization (Docker) and orchestration (Kubernetes).

● Familiarity with Infrastructure as Code (Terraform, Pulumi, CDK).

Soft Skills

Strong architectural thinking and problem-solving in fast-paced delivery environments.

Excellent communication and collaboration skills to work across cross-functional teams and

clients.

Proactive, structured, and detail-oriented with a bias for execution.

Nice to Have

Experience in real-world deployments of Agentic AI systems or collaborative multi-agent setups.

Exposure to regulatory/ethical concerns in AI such as fairness, transparency, or bias mitigation.

Familiarity with AI observability, explainability, and governance tooling (e.g., Arize, Fiddler,

TruEra).

About the Role

We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, MLOps, and Generative AI. The ideal candidate will have hands-on experience in building scalable ML models, deploying them in production, and working with modern AI frameworks, including GenAI technologies.

Key Responsibilities

·      Design, develop, and deploy machine learning models for real-world business problems

·      Work on end-to-end ML lifecycle: data preprocessing, model building, evaluation, deployment, and monitoring

·      Implement and manage MLOps pipelines for scalable and reproducible workflows

·      Utilize tools like MLflow for experiment tracking, model versioning, and lifecycle management

·      Develop and integrate Generative AI (GenAI) solutions such as LLM-based applications

·      Collaborate with cross-functional teams (engineering, product, business) to translate requirements into AI solutions

·      Optimize model performance and ensure production stability

·      Stay updated with the latest advancements in AI/ML and GenAI ecosystems

Required Skills & Qualifications

·      4+ years of experience in Data Science / Machine Learning

·      Strong programming skills in Python

·      Hands-on experience with ML modeling techniques (supervised, unsupervised, NLP, etc.)

·      Solid understanding of MLOps practices and tools

·      Experience with MLflow or similar model lifecycle tools 

·      Practical experience in Generative AI (GenAI), including working with LLMs

·      Experience with libraries/frameworks like Scikit-learn, TensorFlow, PyTorch

·      Strong understanding of data structures, algorithms, and statistics

·      Experience with cloud platforms (AWS/GCP/Azure) is a plus

Good to Have

·      Experience with LLM fine-tuning, prompt engineering, or RAG pipelines

·      Exposure to Docker, Kubernetes, and CI/CD pipelines

·      Knowledge of data engineering workflows 

We are seeking a Senior Data Science & ML Associate with 4+ years of applied ML experience to build and ship models end-to-end from data prep and feature engineering to training, evaluation, and deployment driving measurable business impact.

Key Responsibilities

• Build, train, and evaluate ML and deep-learning models

• Engineer features and prepare data at scale

• Deploy models and monitor production performance

• Partner with stakeholders to frame problems and metrics

• Communicate results and drive decisions

• Iterate on models from business feedback

Mandatory Skills

• 4+ years applied machine learning

• Strong Python (Pandas, NumPy, scikit-learn)

• Classical ML and deep learning (TensorFlow/PyTorch)

• Solid statistics and experiment design

• SQL and data wrangling at scale

• Model deployment / MLOps exposure

Nice to Have: NLP or computer vision; cloud ML (SageMaker, Azure ML)

Senior Product Manager – AI / B2B SaaS

Location: Bengaluru

Work Mode: Work from Office

Experience: 5+ years

Department: Product Management

About LeadSquared

LeadSquared is a leading Sales CRM for high-velocity revenue teams, helping businesses manage leads, sales processes, customer interactions, marketing, and revenue workflows at scale.

We serve businesses where large sales teams manage high volumes of leads and customer interactions, making speed, prioritisation, automation, and effective sales execution critical to revenue growth.

Role Overview

We are looking for a Senior Product Manager – AI to own the roadmap and end-to-end execution of AI products within LeadSquared.

Key Responsibilities

• Own the roadmap, prioritisation, and end-to-end execution for your AI product area.
• Understand customer problems and identify where AI can create meaningful, scalable value and translate them into clear product requirements and scalable solutions.
• Drive products from discovery and 0→1 development through launch, adoption, and iteration.
• Build and scale end-user-facing AI experiences that work reliably within enterprise workflows. 
• Make informed product decisions considering quality, latency, and scale trade-offs in production AI systems.
• Work closely with Engineering, Design, AI/ML, Data, and GTM teams to ship high-quality products.
• Define and track product adoption, engagement, customer outcomes, and business impact.
• Drive GTM, adoption, and continuous product optimisation.

What We're Looking For

• 5+ years of Product Management experience.
• 2+ years of hands-on Product Management experience building AI products.
• Strong B2B SaaS product experience.
• Experience in 0→1 product development and launches.
• Strong product discovery, prioritisation, roadmap management, and execution skills.
• Familiarity with AI evaluations (evals), observability, guardrails, and human oversight.
• Data-driven approach with strong understanding of product metrics.
• Excellent communication, problem-solving, and stakeholder management skills.
• Candidates from Tier 1 / Tier 1.5 / Tier 2 colleges preferred.

Good to Have

• Experience building products using GenAI, LLMs, RAG, AI Agents / Agentic AI, or ML-based decision systems.
• Experience in CRM, SalesTech, MarTech, or Enterprise SaaS.
• Experience building AI products for sales, revenue, operations, or other enterprise users.
• Experience taking an AI capability from an early prototype to a reliable, scalable enterprise product.
• Candidates who have built AI side projects will have a preference. Share links to live products, prototypes, demos, GitHub repositories, agents, or apps you’ve built.
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