About Inizio Ignite

We are Inizio Ignite, the global advisory partner for health and life sciences encompassing connected expertise across Research Partnership, Putnam, STEM, and Vynamic. Guided by purpose, passion, and precision, we collaborate with clients to ignite impact, accelerate performance, and deliver lasting change for patients. By uniting strategy, insights, and innovation with a unique depth and breadth of expertise, we drive transformation and shape the future of health. Proudly part of Inizio – the market-leading commercialization partner for health and life sciences. From early-stage development to loss of exclusivity, we simplify complexity, unlock value, and make collaboration seamless at every pivotal moment – helping healthcare leaders shape strategy and drive meaningful change. 

About the Role

We are seeking an experienced Data Science Manager to join our team at Inizio Ignite. The ideal candidate will bring deep machine learning expertise, strong GenAI and cloud competencies, and hands-on experience delivering analytical solutions that drive meaningful business impact for life sciences clients.

This leader will manage data scientists, oversee project delivery, partner with cross-functional teams, and shape the development of innovative AI/ML solutions.

What you'll be doing

Leadership & Delivery

• Lead and manage a team of data scientists, providing technical guidance, mentorship, and performance oversight.
• Own end-to-end delivery of data science and GenAI engagements for pharma/biotech clients.
• Translate business problems into analytical frameworks and ensure high-quality, timely project execution.
• Drive adoption of AI/ML capabilities across client engagements and internal initiatives.

Technical Responsibilities

• Architect, design, and review ML, statistical, and GenAI solutions, ensuring scalability, accuracy, and alignment with business objectives.
• Oversee the development, validation, and deployment of predictive models, NLP pipelines, and GenAI-based applications (e.g., summarization, insights automation, generative workflows).
• Lead cloud-based solution deployment (AWS, Azure, or GCP) including orchestration, MLOps best practices, and integration with enterprise systems.
• Ensure adherence to model governance, compliance, and responsible AI frameworks.

What you'll need

• Extensive experience in data science or advanced analytics roles, with at least 2–3 years in a leadership or managerial capacity.
• Ideally prior experience in pharmaceutical, biotech, or healthcare consulting is mandatory.
• Strong expertise in machine learning, NLP, deep learning, and GenAI (LLMs, prompt engineering, RAG, fine-tuning, embeddings).
• Hands-on experience with cloud platforms such as AWS, Azure, or GCP; exposure to MLOps frameworks preferred.
• Proficiency in Python, SQL, and common DS/ML libraries (TensorFlow, PyTorch, scikit-learn, Hugging Face, LangChain, etc.).
• Proven experience managing teams, delivering client projects, and presenting to senior stakeholders.
• Good to have understanding of pharma datasets (claims, RWE, clinical, medical insights, social data) and key use cases.
• Experience building GenAI solutions in production environments

Our Pledge

At Inizio, we value inclusivity, recognize the power of diversity, and inspire the next generation of change-makers. We are an equal opportunities employer and are committed to creating a dynamic work environment that values diversity, equity, and inclusion. We welcome all applications regardless of race, color, religion, gender identity, age, national origin, marital status, veteran status, genetic information, sexual orientation, or disability.

Artificial Intelligence

Inizio may use AI technologies to support certain aspects of our recruitment process, but all hiring decisions are made by our human recruiting team. We are committed to fair, inclusive, and human-led hiring practices. Don't meet every requirement? That's okay! We are dedicated to building a diverse, inclusive, and authentic workplace. If you're excited about this role but your experience doesn't perfectly align with every qualification, we encourage you to apply anyway.

Location Details: Gurugram

At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​

This is a hybrid position. You’ll divide your time between working remotely from your home and an office, so you should live within commuting distance. Hybrid teams may work in-office as much as a few times a week or as little as once a month or quarter, as decided by leadership. The hiring manager can share more about what hybrid work might look like for this team.

Join our Team

If you are passionate about machine learning and want to make a difference for millions of small businesses, join our DnAI (Data and Artificial Intelligence) team at GoDaddy as a Senior Machine Learning Scientist. You will have the opportunity to build cutting-edge machine learning models and Generative AI solutions to build intelligent software that delight our customers. You will work with highly skilled engineers in building comprehensive solutions to challenging business problems in customer experience, personalization; as well as solve technical problems in model evaluation, simulation and more.

What you'll get to do...

• Develop and implement advanced machine learning algorithms. 
• Build Intelligent Software using Large Language Models (AI Agents). 
• Design and refine ML models to enhance their performance, scalability, and robustness. 
• Assess, design and curate comprehensive evaluations for open-ended GenerativeAI problems. 
• Collaborate with cross-functional teams to integrate ML solutions within broader product and platform initiatives. 
• Drive the exploration and adoption of cutting-edge ML technologies to maintain our competitive edge in the industry. 

Your experience should include...

• 6+ years of overall experience in machine learning related roles.
• Strong knowledge of machine learning algorithms, tools, and techniques, such as supervised and unsupervised learning, deep learning, computer vision, natural language processing, etc. 
• Familiarity with AI assisted coding tools like Cursor, Claude Code or VS Code. 
• Proficient in Python programming language with familiarity with software engineering best practices, such as version control, code review, CI/CD, etc. 
• Proficiency with prompt engineering and large language models (LLM) and Natural Language Processing (NLP).

You might also have...

• Experience building conversational systems. 
• Experience in designing comprehensive evaluations and verification methods. 
• Proficiency in Typescript is a plus.

We've got your back...  We offer a range of total rewards that may include paid time off, retirement savings (e.g., 401k, pension schemes), bonus/incentive eligibility, equity grants, participation in our employee stock purchase plan, competitive health benefits, and other family-friendly benefits including parental leave. GoDaddy’s benefits vary based on individual role and location and can be reviewed in more detail during the interview process.

We also embrace our diverse culture and offer a range of Employee Resource Groups (Culture). Have a side hustle? No problem. We love entrepreneurs! Most importantly, come as you are and make your own way. 

We encourage you to apply even if your experience or skillset doesn’t align perfectly with every requirement. We value a wide range of backgrounds and transferable skills, and we are excited to support learning and growth.

About us...  GoDaddy is empowering everyday entrepreneurs around the world by providing the help and tools to succeed online, making opportunity more inclusive for all. GoDaddy is the place people come to name their idea, build a professional website, attract customers, sell their products and services, and manage their work. Our mission is to give our customers the tools, insights, and people to transform their ideas and personal initiative into success. To learn more about the company, visit About Us. 

At GoDaddy, we know diverse teams build better products—period. Our people and culture reflect and celebrate that sense of diversity and inclusion in ideas, experiences and perspectives. But we also know that’s not enough to build true equity and belonging in our communities. That’s why we prioritize integrating diversity, equity, inclusion and belonging principles into the core of how we work every day—focusing not only on our employee experience, but also our customer experience and operations. It’s the best way to serve our mission of empowering entrepreneurs everywhere, and making opportunity more inclusive for all. To read more about these commitments, as well as our representation and pay equity data, check out our Diversity and Pay Parity annual report which can be found on our Diversity Careers page.

GoDaddy is proud to be an equal opportunity employer. GoDaddy will consider for employment qualified applicants with criminal histories in a manner consistent with local and federal requirements. Refer to our full EEO policy.

Our recruiting team is available to assist you in completing your application. If they could be helpful, please reach out to myrecruiter@godaddy.com. 

GoDaddy doesn’t accept unsolicited resumes from recruiters or employment agencies.

Role Summary

We are looking for a technically strong AI / ML Developer with hands-on expertise in training and fine-tuning Small Language Models (SLMs) and RAG Solutions. The ideal candidate will drive end-to-end AI Solutions — from dataset curation and pre-processing to training, evaluation, and production deployment. You will collaborate closely with product, product engineers, and infrastructure teams to build AI solutions that are efficient, scalable, and business-aligned.

Key Responsibilities

1  Model Design & Training

• Design, train, and fine-tune Small Language Models (SLMs) using frameworks such as PyTorch, TensorFlow, or JAX.
• Conduct experiments with supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuning.
• Implement efficient training pipelines leveraging distributed training (DDP, FSDP) across GPU/TPU clusters.
• Perform hyperparameter optimisation, ablation studies, and model selection based on benchmark results.
• Develop and maintain data pipelines for collecting, cleaning, tokenising, and pre-processing large-scale training corpora.

2  Model Evaluation & Quality

• Define and implement evaluation frameworks including perplexity, BLEU, ROUGE, BERTScore, and task-specific benchmarks.
• Conduct red-teaming, bias analysis, and safety evaluations to ensure responsible AI deployment.
• Benchmark models against established baselines (e.g., GPT-2, Phi, Mistral) and track performance over iterations.
• Collaborate with QA teams to build regression suites for model versioning and continuous evaluation.

3  MLOps & Deployment

• Containerise and deploy models using Docker, Kubernetes, and cloud-native ML platforms (AWS SageMaker / GCP Vertex AI / Azure ML).
• Build and maintain model registries, experiment tracking (MLflow, Comet), and reproducible training pipelines.
• Optimise inference performance through quantisation (INT8, INT4), pruning, distillation, and ONNX/TensorRT conversion.
• Monitor model drift, data drift, and performance degradation in production; implement automated retraining triggers.

4  Research & Innovation

• Stay current with state-of-the-art NLP/LLM research; prototype and validate new techniques from published literature.
• Contribute to internal knowledge sharing, technical documentation, and model cards.
• Explore parameter-efficient fine-tuning (PEFT) methods such as LoRA, QLoRA, and Adapter layers.
• Investigate and apply mixture-of-experts (MoE), retrieval-augmented generation (RAG), and agentic workflows as needed.

5  Collaboration & Stakeholder Management

• Work with product managers and domain experts to translate business requirements into model objectives and KPIs.
• Communicate model capabilities, limitations, and trade-offs clearly to both technical and non-technical stakeholders.
• Participate in architecture reviews, sprint planning, and cross-functional design discussions.

Required Qualifications

1  Education

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, or a related quantitative field.
• Equivalent professional experience with a strong portfolio of delivered AI/ML projects will be considered.

2  Experience

• 4 – 6 years of professional experience in machine learning or NLP engineering.
• Minimum 2 years of direct, hands-on experience in training or fine-tuning language models (LLMs or SLMs).
• Demonstrable experience taking a model from dataset preparation through to production deployment.

3  Technical Skills — Core

• Programming: Python (proficient); familiarity with C++/CUDA a plus.
• Deep Learning Frameworks: PyTorch (primary), TensorFlow or JAX.
• NLP Libraries: Hugging Face Transformers, Datasets, PEFT, TRL, Accelerate.
• Training Infrastructure: Multi-GPU training, FSDP, DeepSpeed ZeRO stages 1–3.
• Data Engineering: Pandas, NumPy, Apache Spark or Dask for large-scale data prep.
• Vector DBs & Retrieval: FAISS, Pinecone, Weaviate, or equivalent.
• Cloud Platforms: AWS, GCP, or Azure — ML-specific services (SageMaker, Vertex AI, etc.).
• Version Control & CI/CD: Git, GitHub/GitLab, MLflow or W&B for experiment tracking.

4  Technical Skills — Nice to Have

• Experience with multimodal models or vision-language models (VLMs).
• Knowledge of model safety, alignment techniques, and responsible AI frameworks.
• Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks.
• Contributions to open-source ML projects or publications at NeurIPS, ICML, EMNLP, ACL.

Behavioural Competencies

• Intellectual Curiosity: Keeps up with rapidly evolving AI research and applies learnings pragmatically.
• Problem Solving: Approaches ambiguous problems with structured, data-driven thinking.
• Ownership: Takes full accountability for model quality, timelines, and production reliability.
• Collaboration: Works effectively in cross-functional teams with diverse skill sets.
• Communication: Distils complex technical concepts for diverse audiences.
• Adaptability: Thrives in a fast-paced environment where priorities evolve with research breakthroughs.

Job Title: Senior Full Stack Machine Learning Engineer

About Us:

Inovalon is a leading healthcare technology company dedicated to revolutionizing the healthcare industry through innovative AI and machine learning solutions. Our mission is to leverage cutting-edge technology to improve health outcomes and streamline healthcare processes. We are looking for a talented and experienced Senior Full Stack Machine Learning Engineer to join our dynamic team.

Job Description:

• As a Senior Full Stack Machine Learning Engineer, you will play a pivotal role in designing, developing, and deploying machine learning models that drive our healthcare solutions. You will work closely with data scientists, software engineers, and product managers to build scalable and robust machine learning systems. Your expertise will help us transform healthcare data into actionable insights, ultimately improving patient care and operational efficiency.

Key Responsibilities:

• Model Development: Design, implement, and optimize machine learning models for various healthcare applications, including predictive analytics, natural language processing, and generative AI.
• End-to-End Deployment: Develop and maintain the full lifecycle of machine learning solutions, from data preprocessing and model training to deployment and monitoring in production environments.
• Data Engineering: Collaborate with data engineers to build and maintain data pipelines, ensuring the availability of high-quality data for training and inference.
• Software Development: Write clean, efficient, and maintainable code for machine learning applications, ensuring seamless integration with existing systems.
• Performance Optimization: Continuously monitor and improve the performance of machine learning models and systems, addressing issues related to scalability, latency, and accuracy.
• Collaboration: Work closely with cross-functional teams to understand business requirements and translate them into technical solutions.
• Mentorship: Provide guidance and mentorship to junior engineers, fostering a culture of continuous learning and innovation.

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
• Experience: Minimum of 5 years of experience in machine learning, with a proven track record of deploying models in production environments.

Technical Skills:

• Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Proficiency in building applications leveraging generative AI technologies which includes LLM’s, prompt engineering, Vector Databases, RAG architectures and transfer learning is a plus.
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes).
• Strong knowledge of data structures, algorithms, and software engineering best practices.
• Familiarity with big data technologies (e.g., Hadoop, Spark) and data pipeline tools (e.g., Airflow, Kafka).
• Experience with frontend and backend development, including frameworks such as React, Node.js, and Django.

Domain Knowledge: Understanding of healthcare data standards (e.g., HL7, FHIR) and regulations (e.g., HIPAA) is a plus.

Soft Skills:

• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
• Ability to work independently and as part of a team in a fast-paced environment.

What We Offer:

• Competitive salary and benefits package.
• Opportunity to work on impactful projects that improve healthcare outcomes.
• Collaborative and innovative work environment.
• Professional development and growth opportunities.
• Flexible work arrangements, including hybrid and remote options.

Join us in our mission to transform healthcare through technology! We look forward to hearing from you.

About the Role

We're seeking a versatile GenAI Software Engineer who can work across the full stack of GenAI applications, from model integration and prompt engineering to building intuitive user interfaces. You'll build production-ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills.

Key Responsibilities

• Develop end-to-end GenAI features including backend API services, model integration, model monitoring, evaluations and deployments
• Integrate and optimize LLMs for specific use cases in business planning, including prompt engineering, RAG implementation
• Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language
• Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics
• Design and develop APIs that expose AI capabilities to Anaplan's platform and third-party integrations
• Optimize model inference pipelines for performance, cost, and scalability in production environments
• Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour
• Collaborate with data scientists to productionize ML models and forecasting algorithms
• Write comprehensive tests including unit tests, integration tests, and prompt regression suites
• Participate in code reviews, technical design discussions, and knowledge-sharing sessions
• Stay current with GenAI research and tools, evaluating new models and techniques for potential adoption

Required Qualifications

• 3+ years of software engineering experience with 2+ years of understanding on ML/AI systems.
• Strong programming skills in Python including understanding of ML frameworks (PyTorch, TensorFlow, Transformers)
• Understanding or experience of building and deploying LLM-powered applications in production
• Understanding or experience of front-end development with React, TypeScript, and modern web technologies
• Understanding of RESTful API design, microservices architecture, and cloud infrastructure
• Experience with prompt engineering, RAG systems
• Understanding of ML fundamentals including NLP, time-series analysis, or recommender systems
• Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines
• Excellent problem-solving skills and attention to detail
• Bachelor’s degree in computer science, Machine Learning, or related field

Preferred Qualifications

• Experience with GenAI frameworks (LangChain, LlamaIndex, Haystack, or similar)
• Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models
• Experience with model serving frameworks (vLLM, TensorRT, Ray)
• Background in forecasting, planning, or analytics applications
• Familiarity with Anaplan or similar enterprise planning platforms
• Experience with A/B testing and experimentation frameworks for AI features
• Contributions to open-source ML projects or research publications
• Experience with model observability tools (LangSmith, W&B, MLflow)

What Makes This Role Exciting

• Lead a greenfield team building transformative AI capabilities from the ground up
• Work on cutting-edge conversational and agentic AI technologies
• Build user-facing AI features that directly impact how businesses plan and make decisions
• Experiment with the latest GenAI models and techniques
• Collaborate with talented engineers, data scientists, and product designers
• Solve unique challenges at the intersection of AI and enterprise software
• Grow your skills in both ML engineering and full-stack development

About the Role

Are you a tech-savvy organizer who loves finding smarter ways to work?

As our India site continues its rapid scaling, we are looking for a next-generation Executive Assistant to support the India Site Head. This isn’t your traditional administrative role. We are looking for a "tech-first" problem solver who leverages AI agents, automation tools, and large language models to streamline executive operations.

Whether you are an experienced EA looking to modernize your skill set, or a brilliant fresher with a passion for AI and organization, this role is your launchpad. You will be the operational backbone for the Site Head - automating the mundane so the leadership team can focus on the extraordinary, while also bringing a human touch to our operations, serving as the primary host and culture champion for all visiting partners and site gatherings and events.

What You’ll Do

A) AI & Workflow Automation

• Build the "Virtual EA": Deploy and manage AI agents and automation workflows (using tools like Copilot, ChatGPT, Claude, or Power Automate) to handle routine tasks such as calendar triage, meeting invite acceptances, and basic email drafting.
• Smart Follow-Ups: Design automated systems to track leadership action items, pending approvals, and project follow-ups.
• Process Innovation: Continuously research and implement new AI tools to reduce administrative overhead for the executive office.

B) Executive & Site Support

• Strategic Calendar Management: Manage complex scheduling for the Site Head, ensuring time is protected for high-priority business initiatives.
• Event & Delegate Management: Act as the primary host for visiting global executives, VIP delegates, and external partners.
• Culture & People: Organize high-impact site events, leadership offsites, and team-building initiatives that foster a highly engaged work environment.
• Cross-Functional Coordination: Act as a seamless liaison between the Site Head, the Chief of Staff, and the broader GCC leadership team.

What You Bring

• Experience: Open to both fresh graduates with a strong tech portfolio and experienced professionals with a proven track record of modernizing administrative workflows.
• Tech Fluency: Hands-on experience (or strong demonstrated interest) in AI tools, prompt engineering, and basic workflow automation. You don't need to be a software engineer, but you should be extremely comfortable configuring AI agents to solve operational bottlenecks.
• Exceptional Communication: Flawless written and verbal communication skills, with the ability to interact confidently with global leadership and diverse teams.
• Hyper-Organized: An innate ability to manage multiple moving parts, prioritize ruthlessly, and anticipate the needs of the executive office before they arise.
• People Skills: A warm, professional demeanour with a natural talent for hospitality, event hosting, and relationship building.