AI Engineer

AI based systems design and development, entire pipeline from image/ video ingest, metadata ingest, processing, encoding, transmitting.

Implementation and testing of advanced computer vision algorithms.

Dataset search, preparation, annotation, training, testing, fine tuning of vision CNN models. Multimodal AI, LLMs, hardware deployment, explainability.

Detailed analysis of results. Documentation, version control, client support, upgrades.

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.

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

Kody Technolab Limited is seeking an experienced AI/ML Engineer to design, develop, and deploy cutting-edge Artificial Intelligence and Machine Learning solutions. The ideal candidate will have

strong expertise in Machine Learning, Deep Learning, Generative AI, LLMs, MLOps, and cloud-based AI deployments.

Key Responsibilities

• Design, develop, and deploy Machine Learning and Deep Learning models for classification, regression, recommendation systems, NLP, Computer Vision, and Generative AI applications.

• Build and maintain end-to-end ML pipelines including data preprocessing, feature engineering, model training, validation, evaluation, and deployment.

• Develop AI solutions using PyTorch, TensorFlow, Scikit-learn, Hugging Face, and related frameworks.

• Work with Large Language Models (LLMs) and foundation models such as GPT, BERT, Llama, Claude, and Stable Diffusion.

• Collaborate with product, engineering, and business teams to translate requirements into scalable AI solutions.

• Optimize model performance, scalability, and reliability for production environments.

• Implement MLOps best practices using tools such as MLflow, Docker, Kubernetes, and Kubeflow.

• Stay updated with emerging trends and research in AI, ML, Deep Learning, and Generative AI.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field.

• 7+ years of hands-on experience in AI/ML product development.

• Strong proficiency in Python and ML frameworks including Scikit-learn, TensorFlow, PyTorch, and Hugging Face.

• Experience with Generative AI, LLMs, GANs, VAEs, diffusion models, and prompt engineering.

• Strong understanding of the ML lifecycle including model training, tuning, deployment, monitoring, and optimization.

• Experience with MLOps tools such as MLflow, Docker, Kubeflow, and CI/CD pipelines.

• Experience with AWS, Azure, or GCP cloud platforms.

• Strong problem-solving and analytical skills.

Preferred Skills

• Fine-tuning and deployment of Large Language Models.

• Experience with RAG (Retrieval Augmented Generation) architectures.

• Contributions to open-source AI projects or research publications.

• Knowledge of model interpretability, data annotation, and feature engineering.

• C++ experience for high-performance AI applications.

Why Join Kody Technolab Limited?

Opportunity to work on innovative AI products, Generative AI solutions, robotics integrations,

and enterprise-scale applications while collaborating with a highly skilled technology team.

Visit the Website to know more about us.

Company Website - Kody Technolab | Deep Tech Company in Robotics & AI Solution

Kody Robots | Robotics Company in India for Autonomous Robots

Experience: 0–1 Year / Freshers

Location: Remote

Employment Type: Full-Time

About the Role

We are looking for a Junior Software Engineer – AI/ML with hands-on academic, internship, or personal project experience in Core AI/ML.

Key Areas We’re Looking For

• Core AI/ML
• Trading / Finance
• CCTV / Video Analytics
• Face Recognition
• OMR / OCR

Required Skills

• Python and basic Machine Learning concepts
• Experience with AI/ML projects
• Knowledge of OpenCV, Scikit-learn, PyTorch, or TensorFlow
• Basic understanding of model training, evaluation, and data preprocessing
• Git/GitHub

Candidate Profile

• Freshers or candidates with 0–1 year experience
• Practical AI/ML projects preferred
• Should be able to clearly explain their project, model/algorithm, dataset, and individual contribution

Hiring for AI Engineer

Exp: 6 - 8 yrs

Edu : BE/B.Tech/MCA

Work Location : Pune

Skill Set:

- Total experience ranging from 6–8 years in software engineering/AI roles

- Min 5 years strong programming experience in Python is a MUST

- Min 3.5 years hands-on experience in AI with LLMs, RAG pipelines, and AI frameworks

- Experience with cloud platforms (AWS/Azure/GCP)

Role: Principal AI Architect — Multimodal Video Intelligence

Location: India Remote, with overlap with Singapore working hours

Employment Type: Full-time

Reporting to: Founder / CEO

Function: AI Architecture, Multimodal AI, Video Intelligence, Media Representation

About the Client

The client is building an AI-native media intelligence platform that transforms long-form video into structured, searchable, reusable and monetisable media intelligence.

The platform is not simply a video-clipping tool. We are developing a persistent intelligence layer for media, where video, audio, speech, text, objects, scenes, events, entities, emotions, narrative arcs and commercial signals are processed into a reusable representation that can support multiple downstream use cases, including:

• short-form clip generation;
• semantic search;
• scene and narrative understanding;
• contextual advertising;
• shoppable video;
• creator and content analytics;
• automated editing workflows;
• future media-intelligence APIs.

We are looking for a Principal AI Architect who can define and guide the AI architecture behind this platform.

Role Summary

The Principal AI Architect — Multimodal Video Intelligence will own the technical architecture for AI systems, including multimodal video understanding, persistent media representation, model orchestration, evaluation frameworks, and production AI design.

This is a hands-on architecture role. The ideal candidate can move between research papers, model selection, system design, data schemas, prototype review, engineering trade-offs, and implementation guidance.

You will work closely with the Founder / CEO, senior AI engineers, computer vision engineers, backend engineers and external vendors to convert the product and IP vision into a robust technical system.

Key Responsibilities

1. AI System Architecture

• Define the end-to-end AI architecture for long-form video understanding.
• Design the processing pipeline from video ingest to structured media intelligence.
• Define how vision, audio, speech, text, metadata and user signals should be fused.
• Design the architecture for reusable media intelligence rather than one-time clip generation.
• Ensure the system can support multiple downstream applications from the same processed media layer.

2. Persistent Media Representation

• Design persistent media representation layer across multiple levels, including frame, object, shot, scene, segment, entity, event and full-video levels.
• Define what intelligence must be stored permanently versus computed on demand.
• Design schemas for temporal, spatial, semantic, narrative and commercial metadata.
• Define provenance, confidence, model versioning and evidence-tracking requirements.
• Ensure the representation remains usable even when underlying AI models are replaced or upgraded.

3. Multimodal Model Strategy

• Select and evaluate appropriate models for video, image, audio, speech, OCR, entity extraction, scene understanding, action recognition, embeddings, reranking and LLM/VLM reasoning.
• Decide where to use open-source models, commercial APIs, fine-tuning or custom models.
• Define model interfaces so models can be swapped without breaking downstream systems.
• Guide model benchmarking for accuracy, latency, cost and scalability.
• Prevent over-dependence on any single model vendor or API.

4. Temporal and Narrative Intelligence

• Design approaches for understanding long-form video structure, including scenes, events, story arcs, character/entity continuity and engagement peaks.
• Define methods to identify clip-worthy moments across different content types.
• Support narrative scoring, highlight ranking, scene segmentation and coherence validation.
• Ensure that clips are not only visually interesting but contextually and narratively coherent.

5. Evaluation and Benchmarking

• Define objective evaluation frameworks for AI outputs.
• Build or guide creation of benchmark datasets and UAT criteria.
• Define metrics for clip quality, scene accuracy, entity continuity, timestamp alignment, hallucination control, ranking quality, retrieval precision and cost efficiency.
• Establish model and prompt evaluation processes.
• Create regression-testing methodology when models, prompts, schemas or scoring logic change.

6. Search, Retrieval and Knowledge Layer

• Design hybrid search architecture across transcript, visual events, metadata, embeddings and structured knowledge.
• Define when to use relational storage, vector databases, graph databases and object storage.
• Design queryable media intelligence for downstream APIs and applications.
• Support knowledge-graph or ontology-based representation where useful.
• Ensure retrieved outputs are evidence-backed and timestamp-grounded.

7. Production AI Architecture

• Work with AI engineers to convert architecture into deployable services.
• Guide decisions on batching, GPU inference, model serving, queues, retries, observability and cost controls.
• Review pipeline designs involving FFmpeg, GStreamer, DeepStream, TensorRT, Triton, ONNX, cloud services and model APIs.
• Define failure-handling, reprocessing, versioning and rollback mechanisms.
• Support scalable design without premature overengineering.

8. IP and Technical Differentiation

• Help translate AI architecture into defensible technical differentiation.
• Support patent-related technical disclosures where required.
• Identify what is proprietary versus commodity.
• Avoid building a generic wrapper over existing models.
• Ensure the architecture reinforces the core thesis of persistent, reusable media intelligence.

9. Team Guidance

• Provide technical direction to senior AI engineers and computer vision engineers.
• Review designs, experiments, evaluation results and architecture decisions.
• Mentor engineers without becoming a pure people manager.
• Help define technical milestones for the first 90, 180 and 365 days.
• Support hiring, technical interviews and vendor evaluation where needed.

Required Experience

The ideal candidate should have:

• 8+ years of AI/ML experience, with significant exposure to computer vision, video AI, multimodal AI, retrieval systems or production ML architecture.
• Strong experience designing AI systems, not only implementing isolated models.
• Hands-on experience with video understanding, temporal modelling, multimodal pipelines, VLMs, LLMs, embeddings, ranking or retrieval.
• Experience taking AI systems from prototype to production.
• Strong knowledge of Python and modern AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face or equivalent.
• Experience with model evaluation, benchmarking, error analysis and dataset design.
• Understanding of production architecture: APIs, queues, databases, cloud, model serving, observability and deployment trade-offs.
• Ability to work with founders and engineers in a high-ambiguity startup environment.

Strongly Preferred Experience

• Video understanding, action recognition, scene segmentation, event detection or video retrieval.
• Multimodal AI involving video, audio, speech, text and metadata.
• LLM/VLM orchestration for structured outputs.
• Prompt/version management, schema validation and hallucination control.
• Embedding search, vector databases, reranking and retrieval evaluation.
• Knowledge graphs, ontologies, entity resolution or temporal knowledge representation.
• Model serving using TensorRT, Triton, ONNX, vLLM, DeepStream or similar.
• Experience with long-form video, OTT, sports media, entertainment, creator platforms, advertising technology or social commerce.
• Experience contributing to patents, technical disclosures or investor diligence.

Technical Areas

The candidate should be comfortable discussing and making architecture decisions across:

• Computer vision;
• video AI;
• multimodal fusion;
• speech-to-text;
• OCR;
• image/video embeddings;
• VLMs and LLMs;
• semantic search;
• vector databases;
• graph databases;
• temporal reasoning;
• ranking and scoring systems;
• prompt orchestration;
• model evaluation;
• model versioning;
• data lineage;
• GPU inference;
• cloud AI deployment.

What This Role Is Not

This is not a role for someone who has only built:

• chatbots;
• basic RAG demos;
• LangChain prototypes;
• prompt-engineering workflows;
• simple OpenAI/Gemini API wrappers;
• dashboards over model outputs;
• classical computer vision demos without production architecture;
• MLOps pipelines without AI system-design depth.

The role requires architectural depth in AI systems, not just familiarity with AI tools.

First 90-Day Expectations

First 30 Days

• Review product thesis, patent direction, prototype plans and existing technical assumptions.
• Assess current team capability and architecture gaps.
• Define the first version of AI architecture.
• Identify immediate technical risks and validation priorities.

First 60 Days

• Deliver a detailed architecture document covering media representation, model stack, pipeline design, storage strategy, evaluation framework and implementation roadmap.
• Define the canonical media-intelligence schema.
• Define model-selection and benchmarking criteria.
• Guide senior engineers on first implementation milestones.

First 90 Days

• Help the team implement and validate the first working version of the persistent media-intelligence layer.
• Establish evaluation datasets and UAT metrics.
• Review prototype outputs and improve architecture based on evidence.
• Produce a 6-month AI roadmap with technical risks, milestones and resourcing needs.

Success Metrics

The Principal AI Architect will be successful if:

• They have a clear AI architecture that the engineering team can execute.
• The platform does not collapse into a generic clip-generation pipeline.
• The media representation is reusable across multiple use cases.
• Models, prompts and schemas are versioned and testable.
• AI outputs are measurable through objective benchmarks.
• Snehashish, Abhishek and other engineers have clear technical direction.
• The architecture supports both product execution and investor/IP defensibility.

Candidate Personality Fit

The right candidate should be:

• intellectually strong but practical;
• hands-on enough to review code and experiments;
• comfortable with ambiguity;
• willing to challenge assumptions with evidence;
• able to simplify complex AI architecture for engineers and investors;
• disciplined about evaluation, cost and production constraints;
• not attached to one model, tool or vendor;
• able to work in a founder-led early-stage startup. 

Hiring for Junior AI Engineer

Exp : 4 - 6 yrs

Edu : BE/B.Tech/MCA

Work Location : Pune WFO

Skills :

- Min 3 years strong programming experience in Python is a MUST

- Min 2 years hands-on experience in AI with LLMs, RAG pipelines, and AI frameworks

- Experience with cloud platforms (AWS/Azure/GCP)

About the Job :

We are looking for a passionate and driven AI Intern to join our dynamic team. As an intern, you will have the opportunity to work on real-world projects, develop AI models, and collaborate with experienced professionals in the field. This internship is designed to provide hands-on experience in AI and machine learning, offering you the chance to contribute to impactful projects while enhancing your skills.

Job Description:

We are seeking a talented Artificial Intelligence Specialist to join our dynamic team. As an AI Specialist, you will be responsible for developing, implementing, and optimizing AI models and algorithms. You will collaborate closely with cross-functional teams to integrate AI capabilities into our products and services. The ideal candidate should have a strong background in machine learning, deep learning, and natural language processing, with a passion for applying AI to real-world problems.

Responsibilities:

• Design, develop, and deploy AI models and algorithms.
• Conduct data analysis and pre-processing to prepare data for modeling.
• Implement and optimize machine learning algorithms.
• Collaborate with software engineers to integrate AI models into production systems.
• Evaluate and improve the performance of existing AI models.
• Stay updated with the latest advancements in AI research and apply them to enhance our products.
• Provide technical guidance and mentorship to junior team members.

Requirements:

• Any Graduate / Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field; Master's degree preferred.
• Proven experience in developing and implementing machine learning models and algorithms.
• Strong programming skills in languages such as Python, R, or Java.

Benefits :

• Internship Certificate
• Letter of Recommendation
• Performance-Based Stipend
• Part-time work from home (2-3 hours per day)
• 5 days a week, fully flexible shift