Scientist - Natural Language Processing Engineer

We're at the forefront of creating advanced AI systems, from fully autonomous agents that provide intelligent customer interaction to data analysis tools that offer insightful business solutions. We are seeking enthusiastic interns who are passionate about AI and ready to tackle real-world problems using the latest technologies.

We are looking for a passionate AI/ML Intern with hands-on exposure to Large Language Models (LLMs), fine-tuning techniques like LoRA, and strong fundamentals in Data Structures & Algorithms (DSA). This role is ideal for someone eager to work on real-world AI applications, experiment with open-source models, and contribute to production-ready AI systems.

Duration: 6 months

Perks:

- Hands-on experience with real AI projects.

- Mentoring from industry experts.

- A collaborative, innovative and flexible work environment

After completion of the internship period, there is a chance to get a full-time opportunity as AI/ML engineer (6-8 LPA).

Compensation:

- Stipend: Base is INR 8000/- & can increase up to 20000/- depending upon performance matrix.

Key Responsibilities

• Work on Large Language Models (LLMs) for real-world AI applications.
• Implement and experiment with LoRA (Low-Rank Adaptation) and other parameter-efficient fine-tuning techniques.
• Perform model fine-tuning, evaluation, and optimization.
• Engage in prompt engineering to improve model outputs and performance.
• Develop backend services using Python for AI-powered applications.
• Utilize GitHub for version control, including managing branches, pull requests, and code reviews.
• Work with AI platforms such as Hugging Face and OpenAI to deploy and test models.
• Collaborate with the team to build scalable and efficient AI solutions.

Must-Have Skills

• Strong proficiency in Python.
• Hands-on experience with LLMs (open-source or API-based).
• Practical knowledge of LoRA or other parameter-efficient fine-tuning techniques.
• Solid understanding of Data Structures & Algorithms (DSA).
• Experience with GitHub and version control workflows.
• Familiarity with Hugging Face Transformers and/or OpenAI APIs.
• Basic understanding of Deep Learning and NLP concepts.

Python Developer - AI/MLYour Responsibilities

• Develop, train, and optimize ML models using PyTorch, TensorFlow, and Keras.
• Build end-to-end LLM and RAG pipelines using LangChain and LangGraph.
• Work with LLM APIs (OpenAI, Anthropic Claude, Azure OpenAI) and implement prompt engineering strategies.
• Utilize Hugging Face Transformers for model fine-tuning and deployment.
• Integrate embedding models for semantic search and retrieval systems.
• Work with transformer-based architectures (BERT, GPT, LLaMA, Mistral) for production use cases.
• Implement LLM evaluation frameworks (RAGAS, LangSmith) and performance optimization.
• Design and maintain Python microservices using FastAPI with REST/GraphQL APIs.
• Implement real-time communication with FastAPI WebSockets.
• Implement pgvector for embedding storage and similarity search with efficient indexing strategies.
• Integrate vector databases (pgvector, Pinecone, Weaviate, FAISS, Milvus) for retrieval pipelines.
• Containerize AI services with Docker and deploy on Kubernetes (EKS/GKE/AKS).
• Configure AWS infrastructure (EC2, S3, RDS, SageMaker, Lambda, CloudWatch) for AI/ML workloads.
• Version ML experiments using MLflow, Weights & Biases, or Neptune.
• Deploy models using serving frameworks (TorchServe, BentoML, TensorFlow Serving).
• Implement model monitoring, drift detection, and automated retraining pipelines.
• Build CI/CD pipelines for automated testing and deployment with ≥80% test coverage (pytest).
• Follow security best practices for AI systems (prompt injection prevention, data privacy, API key management).
• Participate in code reviews, tech talks, and AI learning sessions.
• Follow Agile/Scrum methodologies and Git best practices.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, AI/ML, or related field.
• 2–5 years of Python development experience (Python 3.9+) with strong AI/ML background.
• Hands-on experience with LangChain and LangGraph for building LLM-powered workflows and RAG systems.
• Deep learning experience with PyTorch or TensorFlow.
• Experience with Hugging Face Transformers and model fine-tuning.
• Proficiency with LLM APIs (OpenAI, Anthropic, Azure OpenAI) and prompt engineering.
• Strong experience with FastAPI frameworks.
• Proficiency in PostgreSQL with pgvector extension for embedding storage and similarity search.
• Experience with vector databases (pgvector, Pinecone, Weaviate, FAISS, or Milvus).
• Experience with model versioning tools (MLflow, Weights & Biases, or Neptune).
• Hands-on with Docker, Kubernetes basics, and AWS cloud services.
• Skilled in Git workflows, automated testing (pytest), and CI/CD practices.
• Understanding of security principles for AI systems.
• Excellent communication and analytical thinking.

Nice to Have

• Experience with multiple vector databases (Pinecone, Weaviate, FAISS, Milvus).
• Knowledge of advanced LLM fine-tuning (LoRA, QLoRA, PEFT) and RLHF.
• Experience with model serving frameworks and distributed training.
• Familiarity with workflow orchestration tools (Airflow, Prefect, Dagster).
• Knowledge of quantization and model compression techniques.
• Experience with infrastructure as code (Terraform, CloudFormation).
• Familiarity with data versioning tools (DVC) and AutoML.
• Experience with Streamlit or Gradio for ML demos.
• Background in statistics, optimization, or applied mathematics.
• Contributions to AI/ML or LangChain/LangGraph open-source projects.

Job Title: AI Engineer

Location: Bengaluru 

Experience: 3 Years 

Working Days: 5 Days

About the Role

We’re reimagining how enterprises interact with documents and workflows—starting with BFSI and healthcare. Our AI-first platforms are transforming credit decisioning, document intelligence, and underwriting at scale. The focus is on Intelligent Document Processing (IDP), GenAI-powered analysis, and human-in-the-loop (HITL) automation to accelerate outcomes across lending, insurance, and compliance workflows.

As an AI Engineer, you’ll be part of a high-caliber engineering team building next-gen AI systems that:

• Power robust APIs and platforms used by underwriters, credit analysts, and financial institutions.
• Build and integrate GenAI agents.
• Enable “human-in-the-loop” workflows for high-assurance decisions in real-world conditions.

Key Responsibilities

• Build and optimize ML/DL models for document understanding, classification, and summarization.
• Apply LLMs and RAG techniques for validation, search, and question-answering tasks.
• Design and maintain data pipelines for structured and unstructured inputs (PDFs, OCR text, JSON, etc.).
• Package and deploy models as REST APIs or microservices in production environments.
• Collaborate with engineering teams to integrate models into existing products and workflows.
• Continuously monitor and retrain models to ensure reliability and performance.
• Stay updated on emerging AI frameworks, architectures, and open-source tools; propose improvements to internal systems.

Required Skills & Experience

• 2–5 years of hands-on experience in AI/ML model development, fine-tuning, and building ML solutions.
• Strong Python proficiency with libraries such as NumPy, Pandas, scikit-learn, PyTorch, or TensorFlow.
• Solid understanding of transformers, embeddings, and NLP pipelines.
• Experience working with LLMs (OpenAI, Claude, Gemini, etc.) and frameworks like LangChain.
• Exposure to OCR, document parsing, and unstructured text analytics.
• Familiarity with model serving, APIs, and microservice architectures (FastAPI, Flask).
• Working knowledge of Docker, cloud environments (AWS/GCP/Azure), and CI/CD pipelines.
• Strong grasp of data preprocessing, evaluation metrics, and model validation workflows.
• Excellent problem-solving ability, structured thinking, and clean, production-ready coding practices.

Job Description: Python Developer

Experience: 2+ Years

Job Location: Nr. Iskcon Mega Mall, SG Highway, Ahmedabad

Timings: 10 AM to 7 PM

Job Description:

Technical Skills :

• Good knowledge of Python with 2+ years of minimum experience 
• Strong understanding of various Python Libraries, APIs, and toolkits. 
• Good experience in Django, Django REST Framework, and Flask framework.
• Understanding of AWS Serverless implementation using Lambda and API Gateway
• Hands-on Experience in Databases like Mysql, PostgreSQL.
• Good experience/understanding in Agentic AI / RAG.
• Proficient in NoSQL document databases especially MongoDB, Redis.
• Stronghold in Data Structures and Algorithm
• Thorough understanding of version control system concepts especially GIT.
• Understanding of the whole web stack and how all the pieces fit together (front-end, database, network layer, etc.) and how they impact the performance of your application.
• Excellent understanding of MVC and OOP. Bonus for the understanding of prevalent design patterns.
• Excellent debugging and optimization skills

Job Responsibilities :

• Building big, robust, scalable, and maintainable applications.
• Debugging, Fixing bugs, Identifying Performance Issues, and Improving App Performance.
• Continuously discover, evaluate, and implement new technologies to maximize development efficiency.
• Handling complex technical issues related to web app development & discussing solutions with the team.
• Developing, Deploying, and maintaining Multistage, Multi-tier applications.
• To write high-performing code and will be participating in key architectural decisions.
• Project Execution & Client Interaction
• Scrum Implementation

Location: Mumbai, Maharashtra, India

Sector: Technology, Information & Media

Company Size: 500 - 1,000 Employees

Employment: Full-Time, Permanent

Experience: 10 - 14 Years (Engineering Leadership)

Level: Engineering Manager / Group EM

ABOUT THIS MANDATE :

Recruiting Bond has been exclusively retained by one of India's most prominent and well-established digital platform organisations operating at the intersection of Technology, Information, and Media to identify and place an exceptional Engineering Manager who can lead engineering teams through an enterprise-wide AI adoption and digital transformation agenda.

This is a high-impact, hands-on leadership role at the nexus of people, product, and technology. The organisation is executing one of the most ambitious AI transformation programmes in its sector and this Engineering Manager will be a core driver of that change. You will lead multiple squads, own engineering delivery end-to-end, embed AI tooling and practices into the team's DNA, and shape the engineering culture of tomorrow.

We are seeking leaders who code when it matters, who build systems and teams with equal conviction, and who view AI not as a trend but as a fundamental shift in how great software is built.

THE OPPORTUNITY AT A GLANCE :

AI-First Engineering Culture :

• Own AI adoption across your squads - from LLM tooling integration to automation-first delivery workflows. Make AI a default, not an afterthought.

Hands-On Engineering Leadership :

• Stay close to the code. Lead architecture reviews, unblock engineers, and set the technical bar - not just the management agenda.

People & Org Builder :

• Grow engineers into leaders. Build squads of 615 across functions. Drive hiring, career frameworks, and a culture of psychological safety.

KEY RESPONSIBILITIES :

1. Hands-On Technical Engagement :

• Remain deeply embedded in the technical work participate in design reviews, architecture decisions, and critical code reviews
• Set and uphold the engineering quality bar : performance benchmarks, security standards, test coverage, and release quality
• Provide technical direction on backend platform strategy, API design, service decomposition, and data architecture
• Identify and resolve systemic technical debt and architectural risks across team-owned services
• Unblock engineers by diving into complex problems debugging, pair programming, and system analysis when it matters
• Own key technical decisions in collaboration with Tech Leads and Principal Engineers; balance pragmatism with long-term sustainability

2. AI Adoption, Integration & Transformation (2026 Mandate) :

• Define and execute the team's AI adoption roadmap - from developer tooling to product-facing AI features
• Champion the integration of GenAI tools (GitHub Copilot, Cursor, Claude, ChatGPT) across the full engineering workflow coding, testing, documentation, incident response
• Embed LLM-powered capabilities into the product : recommendation engines, intelligent search, conversational interfaces, content generation, and predictive systems
• Lead evaluation and adoption of AI-assisted SDLC practices : automated code review, AI-generated test suites, intelligent observability, and anomaly detection
• Partner with Data Science and ML Platform teams to productionise ML models with robust MLOps pipelines
• Build team literacy in prompt engineering, RAG (Retrieval-Augmented Generation), and AI agent frameworks
• Create an experimentation culture : run structured AI pilots, measure productivity impact, and scale what works
• Stay ahead of the AI tooling landscape and advise senior leadership on strategic AI investments and engineering implications

3. People Leadership & Team Development :

• Lead, manage, and grow squads of 6 - 15 engineers across seniority levels (L2 through L6 / Junior through Staff)
• Conduct structured 1 : 1s, career growth conversations, and development planning with every direct report
• Design and execute personalised AI upskilling programmes ensure every engineer develops practical AI fluency by end of 2026
• Build and maintain a high-performance team culture : clarity of ownership, accountability, fast feedback loops, and psychological safety
• Drive performance management fairly and rigorously recognise top performers, manage underperformance constructively
• Lead technical hiring end-to-end : define job requirements, conduct bar-raising interviews, and make data-driven hire decisions
• Contribute to engineering career frameworks and level definitions in partnership with the VP / Director of Engineering

4. Engineering Delivery & Execution Excellence :

• Own end-to-end delivery for multiple product squads from planning and scoping through production release and post-launch stability
• Implement and refine agile delivery frameworks (Scrum, Kanban, Shape Up) calibrated to squad needs and product cadence
• Drive predictable delivery : maintain healthy sprint velocity, manage WIP limits, and ensure dependency resolution across teams.
• Establish and own engineering KPIs : DORA metrics (deployment frequency, lead time, MTTR, change failure rate), uptime SLOs, and velocity trends
• Lead incident management : build blameless post-mortem culture, own RCA processes, and drive systemic reliability improvements
• Balance technical debt repayment with feature velocity negotiate prioritisation transparently with Product leadership

5. Strategic Leadership & Cross-Functional Influence :

• Serve as the primary engineering partner for Product, Design, Data, and Business stakeholders translate ambiguity into executable engineering plans
• Participate in quarterly roadmap planning, capacity forecasting, and OKR definition for engineering teams
• Represent engineering in leadership forums articulate technical constraints, risks, and opportunities in business terms
• Contribute to org-wide engineering strategy : platform investments, build-vs-buy decisions, and shared infrastructure priorities
• Build relationships across geographies (Mumbai HQ + distributed teams) to maintain alignment and delivery cohesion
• Act as a culture carrier and ambassador for engineering excellence, innovation, and responsible AI use

AI TRANSFORMATION LEADERSHIP 2026 EXPECTATIONS :

In 2026, Engineering Managers at this organisation are expected to be active architects of AI transformation not passive observers. The following outlines the specific AI leadership expectations for this role :

AI Developer Productivity

• Drive measurable uplift in developer velocity through AI tooling adoption. Target : 30%+ reduction in code review cycle time and 40%+ increase in test coverage automation by Q3 2026.

LLM & GenAI Product Features

• Own delivery of GenAI-powered product capabilities : intelligent content, semantic search, personalisation, and conversational UX in production, at scale.

AI-Augmented Observability

• Implement AI-driven monitoring and anomaly detection pipelines. Reduce MTTR by leveraging predictive alerting, intelligent runbooks, and auto-remediation scripts.

Team AI Fluency :

• Build mandatory AI literacy across all engineering levels.
• Every engineer understands prompt engineering basics, AI ethics guardrails, and responsible AI deployment practices.

Responsible AI Governance :

• Partner with Security, Legal, and Data Privacy to ensure all AI deployments meet compliance standards, bias mitigation requirements, and explainability benchmarks.

TECHNOLOGY STACK & DOMAIN FAMILIARITY REQUIRED :

• Languages: Java/ Go/ Python/ Node.js /PHP /Rust (must be hands-on in at least 2)
• Cloud: AWS / GCP / Azure (multi-cloud exposure strongly preferred)
• AI & GenAI: OpenAI / Anthropic / Gemini APIs /LangChain /LlamaIndex / RAG / Vector DBs / GitHub
• Copilot: Cursor /Hugging Face
• Containers: Docker /Kubernetes /Helm /Service Mesh (Istio / Linkerd)
• Databases: PostgreSQL /MongoDB / Redis / Cassandra / Elasticsearch / Pinecone (Vector DB)
• Messaging: Apache Kafka /RabbitMQ /AWS SQS/SNS /Google Pub/Sub
• MLOps & DataOps: MLflow /Kubeflow / SageMaker / Vertex AI /Airflow /dbt
• Observability: Datadog /Prometheus /Grafana /OpenTelemetry / Jaeger /ELK Stack
• CI/CD & IaC: GitHub Actions ArgoCD / Jenkins / Terraform /Ansible /Backstage (IDP)

QUALIFICATIONS & CANDIDATE PROFILE :

Education :

• B.E. / B.Tech or M.E. / M.Tech from a Tier-I or Tier-II Institution - CS, IS, ECE, AI/ML streams strongly preferred
• Demonstrated engineering depth and leadership impact may complement institution pedigree

Experience :

• 10 to 14 years of progressive engineering experience, with at least 3 years in a formal Engineering Manager or equivalent people-leadership role
• Proven track record of managing and scaling engineering teams (615+ engineers) in a fast-growing SaaS or digital product environment
• Hands-on backend engineering background must be able to read, write, and critique production code
• Direct experience driving AI/ML feature delivery or AI tooling adoption within engineering organisations
• Exposure across start-up, mid-size, and large-scale product organisations, preferred adaptability is a core requirement
• Strong CS fundamentals: distributed systems, algorithms, system design, and software architecture
• Demonstrated career stability minimum of 2 years of average tenure per organisation.

The Ideal Engineering Manager in 2026 :

• Leads with context, not control, empowers engineers while maintaining accountability and quality
• Is fluent in both people language and technical language, switches registers naturally with engineers and executives alike
• Sees AI as a force multiplier for the team, not a threat. Actively experiments with and advocates for AI tooling
• Measures success by team outcomes, not personal output. Takes pride in what the team ships, not what they build alone
• Creates feedback loops obsessively between product and engineering, between seniors and juniors, between metrics and decisions
• Has strong opinions, loosely held, brings conviction to discussions but updates on evidence
• Invests in engineering excellence as seriously as delivery velocity knows that quality and speed are not opposites

WHY THIS ROLE STANDS APART :

AI Transformation at Scale :

• Lead one of the most significant AI adoption programmes in India's digital media sector.
• Our decisions will shape how hundreds of engineers work in 2026 and beyond.

Hands-On & Strategic Balance :

• A rare EM role that actively encourages technical depth.
• Stay close to the code while owning the people agenda - the best of both worlds.

Established Platform, Real Scale :

• 5001,000 engineers, proven product-market fit, and the org maturity to execute.
• This is not a greenfield startup gamble it is a serious company with serious ambition.

Clear Leadership Growth Path :

• A visible, direct path toward Director / VP of Engineering.
• Senior leadership is invested in growing its next generation of technology executives.

Python Developer at BeyondScale

BeyondScale is a technology company on a mission to democratise AI for small and medium-sized businesses (SMBs). We're building Sitara, an AI-powered ERP suite that is a suite of micro-apps designed specifically for the service sector. Imagine a pocket CRM, a pocket POS, and a suite of essential tools—all streamlined for simplicity and powered by intelligent automation.

The Opportunity:

We're looking for a passionate Python Developer to join our growing team and play a key role in shaping the future of AI-powered ERP. You'll be instrumental in building Sitara, a product poised to disrupt a massive market with high growth potential.

What You'll Do:

• Design, develop, and maintain efficient, reusable, and reliable Python code for our AI-powered ERP platform.
• Develop and integrate web APIs and interact with SQL databases (NoSQL experience a plus).
• Implement automation using object-oriented programming (OOP) principles, multiprocessing, and threading.
• Write clean, well-documented code and actively participate in testing and debugging.
• Leverage Git and modern development workflow practices to ensure a smooth development cycle.
• While not required, familiarity with generative AI concepts (LLMs, RAG) is a plus.

You're a Great Fit If You:

• Have 1+ years of relevant job experience working with Python
• Possess a strong foundation in computer science fundamentals.
• Are a team player with a collaborative spirit and a positive attitude.
• Enjoy learning new technologies and are eager to push boundaries.
• Have excellent communication skills, including the ability to effectively say no when needed.

Job Category: Software Development

Job Type: Full Time

Job Location: Bangalore

Gnani.ai aims to empower enterprises with AI based speech technology.

Gnani.ai is an AI-based Speech Recognition and NLP Startup that is working on voice-based solutions for large businesses. AI is the biggest innovation that is disrupting the market and we are at the heart of this disruption. Funded by one of the largest global conglomerates in the world, and backed a number of market leaders in the tech industry,

We are working with some of the largest companies in the banking, insurance, e-commerce and financial services sectors and we are not slowing down. With aggressive expansion plans, Gnani.ai aims to be the leader in the global market for voice-based solutions.

Gnani.ai is building the future for voice-based business solutions. If you are fascinated by AI and would like to work on the latest AI technologies in a high-intense, fast-growing and flexible work environment with immense growth opportunities, come and join us. We are looking for hard workers, who are ready to take on big challenges.

NLP Software Developer

Gnani.ai is looking to hire software developers with 0 to 2+ Years of experience, with a keen interest in designing and developing chat and voice bots. We are looking for an Engineer who can work with us in developing an NLP framework if you have the below skill set

Requirements :

• Proficient knowledge of Python
• Proficient understanding of code versioning tools, such as Git / SVN.
• Good knowledge of algorithms to find and implement tools for NLP tasks
• Knowledge of NLP libraries and frameworks
• Understanding of text representation techniques, algorithms, statistics
• Syntactic & Semantic Parsing
• Knowledge/work experience on No-SQL database Mongo.
• Good knowledge of Docker container technologies.
• Strong communication skills

Responsibilities :

• Develop NLP systems according to requirements
• Maintain NLP libraries and frameworks
• Design and develop natural language processing systems
• Define appropriate datasets for language learning
• Use effective text representations to transform natural language into useful features
• Train the developed model and run evaluation experiments
• Find and implement the right algorithms and tools for NLP tasks
• Perform statistical analysis of results and refine models
• Constantly keep up to date with the field of machine learning
• Implement changes as needed and analyze bugs

Good To Have :

Start up experience is a plus