Research Scientist - Machine Learning/Artificial Intelligence

Strong AI/ML Engineer profile with experience in GEO work

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Mandatory (Experience 1): Must have 5+ years of experience in rank modelling for GEO

3

Mandatory (Experience 2): Must have 5+ year of experience in GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), or SGE (Search Generative Experience), including optimizing for AI-driven search interfaces, conversational queries, and generative search experiences.

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Mandatory (Experience 3): Must have hands-on exposure to prompt engineering, embeddings, vector search, or RAG-based systems

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Mandatory (Skills 1): Deep understanding of how modern search engines and AI-driven systems rank and generate responses, including semantic search and entity-based optimization

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Mandatory (Skills 2): Exposure to AI/LLM ecosystems such as ChatGPT, Google Gemini, or similar platforms, including understanding of how responses are generated and ranked

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Mandatory (Skills 3): Understanding of content structuring for AI consumption (schema, context building, knowledge representation)

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Mandatory (Education) - B.Tech or Dual degree (Btech and Mtech or Integrated Msc/MS) from Tier 1 Engineering Institutes (IITs, NITs, VIT, BITS, DTU, NSUT)

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Mandatory (Company) - Only Top product companies with high scale (Tier2 companies wont be considered)

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Mandatory (Note) - Output of Candidate's work on AI Engineering for GEO should also be mentioned in resume

AI Engineer (Preferred Years of Experience: 8 years)

We are seeking a highly skilled Full Stack AI Engineer to design, build, and scale intelligent applications across the full technology stack. This role combines strong backend and frontend engineering expertise with applied AI/ML implementation in enterprise cloud environments.

You will work closely with product managers, architects, data scientists, and DevOps teams to deliver production-grade AI-powered solutions that are secure, scalable, and aligned with business objectives.

This is a hands-on engineering role requiring experience across application development, AI model integration, cloud architecture, and DevSecOps practices.

Key Responsibilities

AI / Machine Learning

• Design and implement AI/ML solutions for real-world business use cases.
• Integrate ML models (e.g., forecasting, classification, NLP, computer vision) into production-grade applications.
• Develop APIs and services that expose AI capabilities securely and efficiently.
• Optimize model performance, latency, scalability, and monitoring in production.
• Implement model lifecycle management (training, deployment, monitoring, retraining).

Backend Development

• Design and develop scalable RESTful and/or GraphQL APIs.
• Build microservices-based architectures.
• Implement authentication, authorization, and secure API access.
• Develop data pipelines and integrate with structured and unstructured data sources.
• Ensure high availability, performance tuning, and observability.

Frontend Development

• Develop responsive, user-friendly web applications.
• Build interactive dashboards and AI-driven user experiences.
• Integrate frontend applications with backend AI services.
• Ensure accessibility, usability, and performance optimization.

Cloud & DevOps

• Deploy applications and models in cloud environments (Azure, AWS, or GCP).
• Implement CI/CD pipelines for application and model deployment.
• Apply infrastructure-as-code (Terraform, ARM, Bicep, etc.).
• Implement monitoring, logging, and alerting.
• Ensure security compliance and enterprise-grade governance.

Architecture & Collaboration

• Participate in solution architecture and design discussions.
• Translate business requirements into technical solutions.
• Collaborate with cross-functional teams (product, security, data, UX).
• Contribute to technical standards, best practices, and code reviews.

Required Qualifications

• 8 years of full stack software engineering experience.
• Hands-on AI/ML implementation in production environments.
• Strong proficiency in: Python (FastAPI, Flask, or Django), JavaScript/TypeScript (React, Angular, or Vue), REST API development
• Experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, or equivalent).
• Experience deploying AI workloads in cloud environments (Azure ML, SageMaker, Vertex AI, etc.).
• Experience with relational and NoSQL databases.
• Strong understanding of software engineering principles and design patterns.
• Experience with Docker and container orchestration (Kubernetes preferred).
• Knowledge of secure coding practices and enterprise security standards.

Preferred Qualifications

• Experience with enterprise AI governance and responsible AI frameworks.
• Experience with MLOps and model monitoring tools.
• Knowledge of distributed systems and event-driven architectures.
• Experience with vector databases and semantic search (if applicable to organization).
• Experience in regulated industries (financial services, healthcare, public sector).
• Experience working in Agile/Scrum teams.

Key Competencies

• Strong problem-solving and analytical skills.
• Ability to translate complex AI concepts into scalable technical solutions.
• Excellent communication and stakeholder engagement skills.
• Ownership mindset with the ability to operate independently.
• Strong attention to performance, security, and maintainability.

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 Native Sales & Business Development Intern (3-Month Internship)

Location: Remote (Anywhere in India)

Duration: 3 Months

Employment Type: Internship

About the Role

Are you interested in Sales, Business Development, and AI-powered customer engagement?

We're looking for an AI Native Sales & Business Development Intern to support our growing AI-first IT Services & Product business. You'll gain practical exposure to B2B sales, AI-assisted prospecting, CRM management, client communication, and consultative selling.

This internship is ideal for candidates who enjoy communicating with people, building relationships, and driving business growth.

Key Responsibilities

• Research and identify potential B2B clients using AI-powered prospecting tools.
• Generate qualified leads through LinkedIn, email campaigns, and outbound outreach.
• Schedule discovery meetings with decision-makers.
• Maintain CRM records and sales pipelines.
• Assist in preparing proposals and client presentations.
• Conduct market and competitor research.
• Support the sales team with follow-ups and relationship management.
• Learn consultative selling for AI, Cloud, Software Development, and Digital Transformation services.

Required Skills

• Excellent verbal and written English communication.
• Strong interpersonal skills.
• Basic understanding of Business Development or Sales.
• Familiarity with LinkedIn.
• Ability to conduct online research.
• Willingness to learn AI-powered sales techniques.
• Self-motivated with a proactive attitude.

Preferred Skills

• Lead Generation
• Cold Email Outreach
• CRM tools (HubSpot, Zoho CRM, Salesforce)
• Microsoft Excel / Google Sheets
• Negotiation Skills
• Sales Automation Tools

Who Can Apply?

• Final-year students
• Recent graduates
• Freshers interested in B2B Sales and Business Development
• Candidates looking to build a career in Enterprise Sales

What You'll Learn

• AI-assisted Prospecting
• B2B Enterprise Sales
• CRM Management
• Sales Automation
• Client Relationship Management
• Negotiation Techniques
• Consultative Selling

Performance Metrics

• Qualified leads generated
• Meetings booked
• Opportunities created
• CRM accuracy
• Conversion rate
• Initiative and continuous improvement

What We Offer

• Live client exposure
• Mentorship from experienced professionals
• Internship Certificate
• Letter of Recommendation for top performers
• Opportunity for a Full-time role based on performance

Company: AISpire360 Role: Senior Voice AI Engineer (Independent Contractor, Full-Time Engagement) Location: Remote (India-based preferred; must overlap 4–6 hours daily with London + US Eastern) Engagement: Full-time independent contractor — long-term Compensation: Competitive, paid in USD, monthly. Senior staff-level rates.

About AISpire360

We are building the operating system for medical practices in the US. Our flagship product is ARIA, an AI receptionist that handles inbound and outbound calls, intake, scheduling, eligibility, prior authorization workflows, and after-hours coverage for medical practices. We are in active production deployment with our first practice — a spine surgery practice at the Hospital for Special Surgery in New York. Multiple specialty practices are in our deployment pipeline.

The platform is built to be specialty-agnostic. The voice agent stack is the universal foundation. Knowledge layers (spine surgery, primary care, behavioral health, dermatology, cardiology, pediatrics, etc.) plug in as configuration. One platform, many specialties.

We are venture-backed, founder-led, and shipping. The technical decisions you make here will be in production within weeks.

What You'll Own

You are the technical anchor for the voice agent. You will be responsible for:

Real-time voice system

• Voice agent stack on ElevenLabs Conversational AI (and evaluation of Retell, Vapi, LiveKit alternatives as we scale)
• STT and TTS configuration, voice tuning, language and accent handling
• Turn-taking, barge-in, end-of-speech detection, latency budgets
• Driving end-to-end voice latency below 700ms (we currently target 600ms)
• Quality vs. cost tradeoffs across voice tier selection (Premium / Turbo / Standard)
• Silence-detection optimization for outbound calls (95% silence-discount realization)

HIPAA + PHI infrastructure

• BAA-compliant hosting architecture (AWS-based, BAA in place)
• PHI detection and redaction pipeline (AWS Comprehend Medical + custom pre-filters)
• Encryption in transit and at rest, audit logging, 7-year retention compliance
• Access controls, RBAC, kill-switch infrastructure
• HIPAA Security Rule compliance for technical safeguards

Agent orchestration and tools

• LLM integration (GPT-4o, Claude Sonnet, with model routing for cost optimization)
• Tool calling for scheduling, eligibility checks, prior auth lookups, calendar booking, task creation
• Multi-turn conversation state management
• Multi-topic call handling and structured task generation
• Safety-critical keyword detection and escalation routing

Integrations

• EHR integration (Epic, Athena, eClinicalWorks — at least one in V1)
• Insurance eligibility APIs (Availity, Change Healthcare, payer-specific)
• Calendar integration (Google Calendar, Microsoft 365, Cal.com)
• SMS and email gateways (Twilio, SendGrid)
• Practice-specific webhooks for task manager surfacing

Multi-tenant platform foundations

• Per-practice configuration loading (specialty profile + practice profile)
• Per-tenant isolation, data segregation
• Specialty-specific intake schemas, triage rules, safety keywords
• Production observability (tracing, metrics, latency monitoring per practice)

Required Experience

You should be able to demonstrate, in a live walkthrough with code in hand, that you have shipped production voice AI systems. Specifically:

• 3+ years of production voice/conversational AI experience. Not chatbots — actual real-time voice agents handling live phone calls. ElevenLabs, Retell, Vapi, LiveKit, OpenAI Realtime, Deepgram, or equivalent.
• Deep familiarity with at least 2 of: ElevenLabs Conversational AI, Retell AI, Vapi, LiveKit Agents, OpenAI Realtime API. Production deployment experience required, not demo experience.
• HIPAA and PHI handling experience in production. Not theoretical. You have signed BAAs, deployed in HIPAA-compliant environments, and built PHI redaction pipelines.
• AWS infrastructure expertise. Specifically: ECS or Fargate, Lambda, S3 with encryption, KMS, CloudWatch, IAM, VPC, BAA-eligible service selection.
• AWS Comprehend Medical or equivalent PHI detection experience.
• Twilio or equivalent telephony provider experience. SIP trunking, inbound/outbound call flows, recording and transcription pipelines.
• Latency optimization in real-time systems. You have hit sub-700ms voice latency in production and can explain the trade-offs you made.
• LLM production experience. GPT-4o, Claude, or equivalent. Prompt engineering, tool calling, structured outputs, model routing for cost.
• Python or TypeScript fluency. Production code, not scripts.
• API integration experience. REST, webhooks, OAuth, async patterns. Bonus if you've integrated with EHRs (Epic FHIR, Athena, eClinicalWorks).

Nice to Have

• Healthcare domain experience (EHRs, clinical workflows, medical terminology)
• Prior auth or eligibility verification workflow experience
• Multi-tenant SaaS architecture experience
• SOC 2 audit experience
• Experience with knowledge graphs (PostgreSQL + pgvector, Neo4j, or similar)
• Open-source contributions to LangChain, LiveKit, Pipecat, or similar voice/agent frameworks
• Demonstrated ability to ship to production fast (not perfectionism — pragmatic engineering)

What This Engagement Looks Like

• Independent contractor. You invoice us monthly. We pay in USD via wire transfer or Wise.
• Full-time engagement. This is your primary work. We expect ~40 hours/week of focused output.
• Long-term. We are not looking for a 3-month engagement. Expect this to run 12+ months.
• You sign a BAA with us. This is non-negotiable due to the nature of the work.
• You are eligible for future equity grants as we formalize the team structure.
• Direct working relationship with our CTO (London-based) and founders (NYC and India).
• Time-zone overlap required: at least 4–6 hours of daily overlap with both London and US Eastern. Indian Standard Time evenings (6 PM IST onward) work well.

How We'll Evaluate You

Our hiring process is fast and substantive. No take-homes. No multi-round bureaucracy.

1. Initial screen (30 min): Background, what you've shipped, compensation expectations, BAA-readiness.
2. Technical deep-dive (90 min): Walk us through a production voice AI system you've shipped. Code in hand. Architecture diagrams. Real production numbers — latency, cost per call, scale. We will ask follow-up questions about specific decisions you made.
3. System design (90 min, live): We give you a design problem — a HIPAA-compliant voice agent for a medical specialty we don't yet support. You design end-to-end on a whiteboard / Excalidraw. We probe trade-offs.
4. Founders + CTO conversation (60 min): Mutual fit. You ask us hard questions. We answer honestly.

Total: 4–5 hours of your time. We'll move from first conversation to offer in 7–10 days for the right candidate.

What We Will NOT Accept

• Take-home assignments produced by other AI tools. We will ask you to walk through code live; if you can't explain decisions you didn't make, the interview ends.
• Resume claims you can't substantiate. We verify employment via EPFO/UAN where applicable.
• "I've done LLM chatbots" experience without production voice agent experience. They are not the same skill.
• Engagement structures that conflict with this being your primary work.

How to Apply

Send a brief message with:

1. A link to a production voice AI system you've shipped (or, if NDA'd, a description of the architecture and your specific contribution).
2. Two or three sentences on why this role fits you specifically — not a generic cover letter.
3. Your current compensation expectation in USD per month.
4. Your earliest start date and current time-zone availability.

We read every message. We respond within 5 business days, including with "no" answers. We don't ghost.

Senior Data Scientist

Your goal: To improve the education process and improve the student experience through data.

The organization: Data Science for Learning Services Data Science and Machine Learning are core to Chegg. As a Student Hub, we want to ensure that students discover the full breadth of learning solutions we have to offer to get full value on their learning time with us. To create the most relevant and engaging interactions, we are solving a multitude of machine learning problems so that we can better model student behavior, link various types of content, optimize workflows, and provide a personalized experience.

The Role: Senior Data Scientist

As a Senior Data Scientist, you will focus on conducting research and development in NLP and ML. You will be responsible for writing production-quality code for data product solutions at Chegg. You will lead in identification and implementation of key projects to process data and knowledge discovery.

Responsibilities:

• Translate product requirements into AIML/NLP solutions

• Be able to think out of the box and be able to design novel solutions for the problem at hand

• Write production-quality code

• Be able to design data and annotation collection strategies

• Identify key evaluation metrics and release requirements for data products

• Integrate new data and design workflows

• Innovate, share, and educate team members and community

Requirements:

• Working experience in machine learning, NLP, recommendation systems, experimentation, or related fields, with a specialization in NLP • Working experience on large language models that cater to multiple tasks such as text generation, Q&A, summarization, translation etc is highly preferred

• Knowledge on MLOPs and deployment pipelines is a must

• Expertise on supervised, unsupervised and reinforcement ML algorithms.

• Strong programming skills in Python

• Top data wrangling skills using SQL or NOSQL queries

• Experience using containers to deploy real-time prediction services

• Passion for using technology to help students

• Excellent communication skills

• Good team player and a self-starter

• Outstanding analytical and problem-solving skills

• Experience working with ML pipeline products such as AWS Sagemaker, Google ML, or Databricks a plus.

Why do we exist?

Students are working harder than ever before to stabilize their future. Our recent research study called State of the Student shows that nearly 3 out of 4 students are working to support themselves through college and 1 in 3 students feel pressure to spend more than they can afford. We founded our business on provided affordable textbook rental options to address these issues. Since then, we’ve expanded our offerings to supplement many facets of higher educational learning through Chegg Study, Chegg Math, Chegg Writing, Chegg Internships, Thinkful Online Learning, and more, to support students beyond their college experience. These offerings lower financial concerns for students by modernizing their learning experience. We exist so students everywhere have a smarter, faster, more affordable way to student.

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Chegg out our culture and benefits!

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Chegg is an equal-opportunity employer

• Proficient in R and Python
• Work experience 1+ years with at least 6 months working with Python
• Prior experience with building ML models
• Prior experience with SQL
• Knowledge of statistical techniques
• Experience with working on Spatial Data will be an added advantage