BOLD is seeking a senior professional to implement and run Testing and Quality Assurance specifically designed for AI-driven products and Data Science workflows. In this role, you will bridge the gap between traditional software testing and modern machine learning evaluation. You have a great team management and organizational skills. You’ll have a broad mastery of capabilities, techniques, technologies and tools in the Testing and QA domains. You’ll be handling QA teams of various sizes and expertise.

ABOUT THIS TEAM

The Data Science department at BOLD is responsible for discovering patterns and trends in datasets to get insights, creating predictive algorithms and data models, improving the quality of data or product offerings by utilizing machine learning techniques, distributing suggestions to other teams and top management, and using data tools such as Python and SQL.

The Data Science team actively collaborates with other vertical teams such as Engineering, Portals, BI, Product, Legal. Most of the projects are focused around problems that require a mix of natural language processing and machine learning. Some of the active projects are resume parsing, ranking, summary generation, data quality and scoring, content generation, job recommendations, and conversion analysis. Apart from the business initiatives, the team also explores state of the art methods and keeps them up to to date with technology.

WHAT YOU’LL DO 

• Develop and own the QA strategy for AI-driven features, focusing on model accuracy, data drift, and performance metrics (Precision, Recall, F1-score).
• Implement state-of-the-art AI tools (e.g., GitHub Copilot, or custom LLM agents) to automate test case generation, code analysis, and synthetic data creation.
• Oversee the testing of Generative AI outputs, implementing "LLM-as-a-judge" frameworks to evaluate hallucination rates, toxicity, and prompt adherence.
• Develop and own BOLD’s quality framework from product development through to production
• Should be able to drive the initiatives (both Business and QA) in his area along with needed smooth coordination across the board to ensure a timely achievement of goal.
• Take part in Requirement Analysis, Sprint planning, Bug triage meetings.
• Liaise with product, development, and infrastructure teams to collaborate on delivery of high quality, high performance, and high availability applications
• Develop quality scripts with needed coverage to ensure defect free releases.
• Manage and mentor team members to maximize output and efficiency and promote a team culture of quality and fun
• Motivate, Encourage, Guide Teams maintaining equilibrium and satisfaction level.
• Give technical/logical solutions to problems faced by the teams and remove hurdles blocking releases.
• Evaluate and suggest new tools and technologies

WHAT YOU’LL NEED

• Solid understanding of the Machine Learning lifecycle (EDA, Training, Evaluation, Deployment).
• Experience using LLMs (GPT, Claude, Llama) and AI-coding assistants to accelerate the testing lifecycle.
• Experience in a high volume, high throughput web/ecommerce environment.
• Hands-on experience with UI/API automation (Selenium, Playwright, or Cypress) integrated with AI-driven healing capabilities.
• Experience with web service technology like XML, REST, SOAP
• Knowledge on any of the query language like SQL, JQL etc.
• Experience in testing complex web and mobile apps.
• Strong application architecture and technical knowledge
• Strong knowledge of web concepts, including web performance infrastructure.
• Able to play the role of a scrum master, with strong coordination skills
• Knowhow of basic UX standards, SEO/ SEM concepts and key tracking matrices
• Strong communication skills 

EXPERIENCE- 

• Module Lead, QA (AI/ML & Automation)- 5 years+

BOLD is seeking for newest addition to our existing Data Science team, you’ll combine your analytical skills and business knowledge to deliver key insights to our Product and Management teams. You’ll help drive product development using our vast user data sets to enhance our current products and to help us find inferences and relationships in this data to build new products – More towards the role required

ABOUT THIS TEAM

The Data Science department at BOLD is responsible for discovering patterns and trends in datasets to get insights, creating predictive algorithms and data models, improving the quality of data or product offerings by utilizing machine learning techniques, distributing suggestions to other teams and top management, and using data tools such as Python and SQL.

The Data Science team actively collaborates with other vertical teams such as Engineering, Portals, BI, Product, Legal. Most of the projects are focused around problems that require a mix of natural language processing and machine learning. Some of the active projects are resume parsing, ranking, summary generation, data quality and scoring, content generation, job recommendations, and conversion analysis. Apart from the business initiatives, the team also explores state of the art methods and keeps them upto to date with technology.

WHAT YOU’LL DO 

• Demonstrate ability to work on data science projects involving predictive modelling, NLP, statistical analysis, vector space modelling, machine learning etc. 
• Leverage our rich data sets of user data to perform research, develop models and create data products with our Development & Product teams 
• Develop novel and scalable data systems in cooperation with our system architects that leverage datasets using machine learning techniques to enhance the user experience 

WHAT YOU’LL NEED 

• Knowledge and experience using statistical and machine learning algorithms including regression, instance-based learning, decision trees, Bayesian statistics, clustering, neural networks, deep learning, ensemble methods 
• Expert knowledge in Python.  
• Practical LLM/RAG experience for search quality  such as  query understanding, semantic retrieval, reranker design .  
• Experience with frameworks that optimizes prompt engineering (langChain/crewai/etc) 
• Experience with Solr/OpenSearch/Elasticsearch … 
• Experience with embedding & vector search  
• Should have done one or more projects involving fine-tuning with LLMs 
• Experience in feature selection, building and optimising classifiers. 
• Experience working with backend technologies such as Flask/ Gunicorn etc. 
• Experience on working with open source library such Spacy,NLTK,Gensim etc  
• Experience on working with deep-learning library such as Tensor flow, Pytorch etc  
• Experience with software stack components including common programming languages, back-end technologies, database modelling, continuous integration, services oriented architecture, software testability etc. 
• Be a keen learner and enthusiastic about developing software.    

EXPERIENCE- 

• Software Engineer- 2.5 years+
• Senior Software Engineer-4.5 years+

#LI-SV1

WHO YOU ARE

You are a passionate Python and AI/ML Engineer minimum 4 years of hands-on experience building intelligent systems. You thrive in fast-paced environments, love solving complex problems with data and algorithms, and take pride in delivering AI solutions that create real business impact. You have experience with cutting-edge Generative AI, scalable ML pipelines, and production-grade systems and you're energized by working at the frontier of what AI can do.

WHAT YOU'LL DO

1. Design, develop, and deploy machine learning models and Generative AI solutions — including classification, clustering, summarization, search & ranking, and information extraction.
2. Own end-to-end ML pipelines — from data ingestion and preprocessing through model training, deployment, and production monitoring.
3. Collaborate with cross-functional teams to translate business requirements into AI-driven features — applying NLP, outlier detection, and deep learning techniques where applicable.
4. Build robust, scalable, and well-documented Python-based RESTful APIs to expose ML models and AI services in production environments.
5. Optimize database interactions and ensure efficient data storage and retrieval for AI applications across SQL and NoSQL systems.
6. Stay current with the latest advances in AI/ML — integrating emerging approaches such as RAG pipelines, LLM fine-tuning, and vector search into live products.

WHAT YOU'LL NEED 

Python
Strong hands-on proficiency for building, scripting, and deploying AI/ML systems.
NumPy · Pandas · FastAPI · Scikit-learn
Machine Learning
Applied expertise across supervised, unsupervised, and deep learning — classification, clustering, outlier detection.
PyTorch · TensorFlow · XGBoost · DBSCAN

Generative AI (2+ yrs)
Hands-on experience building with LLMs — prompt engineering, RAG pipelines, summarization, and AI-powered features.
LLMs · RAG · Prompt Eng. · Fine-tuning

NLP & Search / Ranking
Processes language and builds relevance engines — NER, embeddings, semantic search, and ranking models.
spaCy · BERT · FAISS · Elasticsearch

API Development
Designs and ships secure, well-documented RESTful APIs exposing ML models as production-ready services.
REST · FastAPI · OAuth2 · Swagger

Databases
Proficient in SQL and NoSQL stores for structured and unstructured data pipelines supporting AI workloads.
PostgreSQL · MongoDB · Vector DBs

GOOD TO HAVE

Cloud Platforms
Deploys and scales AI workloads on AWS, Azure, or GCP.
AWS · Azure

TypeScript / JavaScript
Frontend or full-stack exposure for building ML-powered product interfaces.
TypeScript · React · Node.js

MLOps
Manages the ML lifecycle — tracking, versioning, and pipeline automation.
MLflow · Kubeflow · CI/CD

Containerization & Orchestration
Packages and scales AI services using containers and cluster management.
Docker · Kubernetes

WHO YOU ARE

You are a passionate Python and AI/ML Engineer minimum 4 years of hands-on experience building intelligent systems. You thrive in fast-paced environments, love solving complex problems with data and algorithms, and take pride in delivering AI solutions that create real business impact. You have experience with cutting-edge Generative AI, scalable ML pipelines, and production-grade systems and you're energized by working at the frontier of what AI can do.

WHAT YOU'LL DO

1. Design, develop, and deploy machine learning models and Generative AI solutions — including classification, clustering, summarization, search & ranking, and information extraction.
2. Own end-to-end ML pipelines — from data ingestion and preprocessing through model training, deployment, and production monitoring.
3. Collaborate with cross-functional teams to translate business requirements into AI-driven features — applying NLP, outlier detection, and deep learning techniques where applicable.
4. Build robust, scalable, and well-documented Python-based RESTful APIs to expose ML models and AI services in production environments.
5. Optimize database interactions and ensure efficient data storage and retrieval for AI applications across SQL and NoSQL systems.
6. Stay current with the latest advances in AI/ML — integrating emerging approaches such as RAG pipelines, LLM fine-tuning, and vector search into live products.

WHAT YOU'LL NEED 

Python
Strong hands-on proficiency for building, scripting, and deploying AI/ML systems.
NumPy · Pandas · FastAPI · Scikit-learn
Machine Learning
Applied expertise across supervised, unsupervised, and deep learning — classification, clustering, outlier detection.
PyTorch · TensorFlow · XGBoost · DBSCAN

Generative AI (2+ yrs)
Hands-on experience building with LLMs — prompt engineering, RAG pipelines, summarization, and AI-powered features.
LLMs · RAG · Prompt Eng. · Fine-tuning

NLP & Search / Ranking
Processes language and builds relevance engines — NER, embeddings, semantic search, and ranking models.
spaCy · BERT · FAISS · Elasticsearch

API Development
Designs and ships secure, well-documented RESTful APIs exposing ML models as production-ready services.
REST · FastAPI · OAuth2 · Swagger

Databases
Proficient in SQL and NoSQL stores for structured and unstructured data pipelines supporting AI workloads.
PostgreSQL · MongoDB · Vector DBs

GOOD TO HAVE

Cloud Platforms
Deploys and scales AI workloads on AWS, Azure, or GCP.
AWS · Azure

TypeScript / JavaScript
Frontend or full-stack exposure for building ML-powered product interfaces.
TypeScript · React · Node.js

MLOps
Manages the ML lifecycle — tracking, versioning, and pipeline automation.
MLflow · Kubeflow · CI/CD

Containerization & Orchestration
Packages and scales AI services using containers and cluster management.
Docker · Kubernetes

BOLD is seeking for the newest addition to our existing Data Science team, you’ll combine your analytical skills and business knowledge to deliver key insights to our Product and Management teams. You’ll help drive product development using our vast user data sets to enhance our current products and to help us find inferences and relationships in this data to build new products – More towards the role required. 

ABOUT THIS TEAM

The Data Science department at BOLD is responsible for discovering patterns and trends in datasets to get insights, creating predictive algorithms and data models, improving the quality of data or product offerings by utilizing machine learning techniques, distributing suggestions to other teams and top management, and using data tools such as Python and SQL.

The Data Science team actively collaborates with other vertical teams such as Engineering, Portals, BI, Product, Legal. Most of the projects are focused around problems that require a mix of natural language processing and machine learning. Some of the active projects are resume parsing, ranking, summary generation, data quality and scoring, content generation, job recommendations, and conversion analysis. Apart from the business initiatives, the team also explores state of the art methods and keeps them upto to date with technology.

WHAT YOU’LL DO 

• Demonstrate ability to work on data science projects involving NLP, large language models, predictive modelling, statistical analysis, vector space modelling, machine learning etc. 
• Leverage our rich data sets of user data to perform research, develop models and create data products with our Development & Product teams 
• Develop novel and scalable data systems in cooperation with our system architects that leverage datasets using machine learning techniques to enhance the user experience 
• Collaborates effectively with cross-functional teams to deliver end-to-end products & features. 
• Demonstrates ability to multi-task and re-prioritize responsibilities based on changing requirements. 
• Estimates efforts, identify risks, devises and meets project schedules. 
• Runs review meetings effectively and drive the closure of all open issues on time. 
• Evolve prompt engineering applications and benchmark different Large Language models to solve business problems.                  
• Mentors/coaches data scientists to facilitate their development and provide technical leadership to them. 
• Implement and experiment with agentic workflows to improve the job seeker experience. 
• Rises above detail to see broader issues and implications for whole product/team.  

WHAT YOU’LL NEED

• Should be able to handle a team of 2-5 members, if required. 
• Knowledge and experience using statistical and machine learning algorithms, including regression, instance-based learning, decision trees, Bayesian statistics, clustering, neural networks, deep learning, ensemble methods 
• Expert knowledge in Python.  
• Experience with frameworks that optimizes prompt engineering (langChain/crewai/etc) 
• Practical LLM/RAG experience for search quality  such as  query understanding, semantic retrieval, reranker design .  
• Experience with Solr/OpenSearch/Elasticsearch … 
• Experience with embedding & vector search  
• Experience in using large language models. 
• Experience with distributed, semantic and vector based search and match systems.  
• Experience with prompt engineering, chain-of-thought, retrieval augmented generation, vector databases and preferably LLM agents. 
• Experience in feature selection, building and optimizing classifiers. 
• Experience with software stack components, including common programming languages, back-end technologies, database modelling, continuous integration, services-oriented architecture, software testability, etc. 
• Langchain and/or Llamaindex. 
• Be a keen learner and enthusiastic about developing software. 
   

EXPERIENCE- 

• Project Lead, Data Science- 8 years+

#LI-SV1

BOLD is seeking for newest addition to our existing Data Science team, you’ll combine your analytical skills and business knowledge to deliver key insights to our Product and Management teams. You’ll help drive product development using our vast user data sets to enhance our current products and to help us find inferences and relationships in this data to build new products – More towards the role required

ABOUT THIS TEAM

The Data Science department at BOLD is responsible for discovering patterns and trends in datasets to get insights, creating predictive algorithms and data models, improving the quality of data or product offerings by utilizing machine learning techniques, distributing suggestions to other teams and top management, and using data tools such as Python and SQL.

The Data Science team actively collaborates with other vertical teams such as Engineering, Portals, BI, Product, Legal. Most of the projects are focused around problems that require a mix of natural language processing and machine learning. Some of the active projects are resume parsing, ranking, summary generation, data quality and scoring, content generation, job recommendations, and conversion analysis. Apart from the business initiatives, the team also explores state of the art methods and keeps them upto to date with technology.

WHAT YOU’LL DO 

• Demonstrate ability to work on data science projects involving NLP, large language models, predictive modelling, statistical analysis, vector space modelling, machine learning etc. 
• Leverage our rich data sets of user data to perform research, develop models and create data products with our Development & Product teams 
• Develop novel and scalable data systems in cooperation with our system architects that leverage datasets using machine learning techniques to enhance the user experience 
• Collaborates effectively with cross functional teams to deliver end-to-end products & features. 
• Demonstrates ability to multi-task and re-prioritize responsibilities based on changing requirements. 
• Estimates efforts, identify risks, devises and meets project schedules. 
• Runs review meetings effectively and drive the closure of all open issues on time 
• Mentors/coaches data scientists to facilitate their development and provide technical leadership to them. 
• Rises above detail to see broader issues and implications for whole product/team. 

WHAT YOU’LL NEED

• Knowledge and experience using statistical and machine learning algorithms including regression, instance-based learning, decision trees, Bayesian statistics, clustering, neural networks, deep learning, ensemble methods 
• Expert knowledge in Python.  
• Practical LLM/RAG experience for search quality  such as  query understanding, semantic retrieval, reranker design. 
• Experience with Solr/OpenSearch/Elasticsearch .
• Experience with frameworks that optimizes prompt engineering (langChain/crewai/etc) 
• Experience with embedding & vector search  
• Experience in using large language models. 
• Experience in feature selection, building and optimising classifiers. 
• Experience working with backend technologies such as Flask/ Gunicorn etc. 
• Experience on working with open source library such Spacy,NLTK,Gensim etc  
• Experience on working with deep-learning library such as Tensor flow, Pytorch etc  
• Experience with software stack components including common programming languages, back-end technologies, database modelling, continuous integration, services oriented architecture, software testability etc. 
• Be a keen learner and enthusiastic about developing software.  

EXPERIENCE- 

• Module Lead, Data Science- 5.5 years

#LI-SV1

BOLD is seeking for the newest addition to our existing Data Science team, you’ll combine your analytical skills and business knowledge to deliver key insights to our Product and Management teams. You’ll help drive product development using our vast user data sets to enhance our current products and to help us find inferences and relationships in this data to build new products – More towards the role required

ABOUT THIS TEAM

The Data Science department at BOLD is responsible for discovering patterns and trends in datasets to get insights, creating predictive algorithms and data models, improving the quality of data or product offerings by utilizing machine learning techniques, distributing suggestions to other teams and top management, and using data tools such as Python and SQL.

The Data Science team actively collaborates with other vertical teams such as Engineering, Portals, BI, Product, Legal. Most of the projects are focused around problems that require a mix of natural language processing and machine learning. Some of the active projects are resume parsing, ranking, summary generation, data quality and scoring, content generation, job recommendations, and conversion analysis. Apart from the business initiatives, the team also explores state of the art methods and keeps them upto to date with technology.

WHAT YOU’LL DO 

• Build AIML models that serve for content generation, content recommendation, and content moderation using LLMs. 
• Responsible for converting business requirements into robust data science algorithms. 
• Responsible for providing technical leadership to a team of data science engineers. 
• Responsible for design, development, deployment of AI/ML, NLP, statistical & content recommendation algorithms that may not require LLMs.  
• Leverage our rich data sets of user data to perform research, develop models and create data products with our Development & Product teams 
• Develop novel and scalable data systems in cooperation with our system architects that leverage datasets using machine learning techniques to enhance the user experience 
• Collaborates effectively with cross functional teams to deliver end-to-end products & features. 
• Demonstrates ability to multi-task and re-prioritize responsibilities based on changing requirements. 
• Responsible for creating model validation framework. 
• Leading a data science team that delivers actionable results through the combination of data science solutions, business skills, statistical knowledge, and understanding of data. 
• Distilling complex analytical results into presentable, digestible, and actionable feedback for product and engineering teams. 
• Recruit, build and retain a top-tier data science team that brings together top talent at all levels, cutting edge technology, and analytic innovation. 
• Assess, inspire and motivate a high performing team of data science professionals. 

WHAT YOU’LL NEED

• Proven experience in solving open-ended business problems using data-science/ML/AI from initial ideation stage up to delivering the ready-to-use solution. 
• Strong Programming experience in Python. Familiar with various Machine Learning algorithms and Statistical methods. 
• 10+ yrs of working experience in MLData science with NLP background  
• Experience with frameworks that optimizes prompt engineering (langChain/crewai/etc) 
• Must have delivered multiple data science product(s) in production. Deployment with LLMs is a plus. 
• Practical LLM/RAG experience for search quality  such as  query understanding, semantic retrieval, reranker design .  
• Experience with Solr/OpenSearch/Elasticsearch … 
• Experience with embedding & vector search  
• Experience designing and implementing ML systems with Data Pipelines (Data Cleaning and creative Feature Engineering), Model Iterations and Evaluation, High throughput ML(Model Training, Evaluation, GPU vs CPU, XGBoost ML), Python ML Libs(TensorFlow, PyTorch). 
• Experience in leading a team of 3-5 data scientists. 
• Experience using tools to deploy models into the production environment such as Jenkins 

 EXPERIENCE- 

• Engineering Manager, Data Science- 10 years+

#LI-SV1

WHO YOU ARE:

We’re seeking a forward-thinking AI Product Manager with strong technical depth in Machine Learning, LLM-based products, Automation, and API-driven platform design. In this role, you will define, build, and scale AI-powered solutions across Zinnia’s digital insurance platform, enhancing underwriting, claims, operations, and customer engagement workflows.

You’ll work at the intersection of AI innovation, insurance expertise, and engineering execution, translating business needs into scalable products that deliver measurable impact.

WHAT YOU’LL DO:

• Contribute to the product vision and roadmap for AI/ML initiatives across Zinnia’s platform.
• Identify high-impact opportunities to integrate AI into insurance value chains (underwriting, policy admin, claims, distribution, agent enablement).
• Evaluate new AI technologies - Agentic AI, Gen AI (LLMs, RAG, predictive analytics, automation frameworks) and drive adoption across the organization.
• Translate user problems and business needs into clear product requirements, PRDs, and user stories.
• Work closely with engineering, data science, design, actuarial, and insurance SMEs to ship high-quality AI products.
• Drive API-first development for system integrations with carriers, distributors, third-party data providers, and internal platforms.
• Ensure AI and APIs follow robust security, compliance, and governance guidelines—especially relevant to Life & Annuities.

AI/ML Technical Collaboration:

• Understand ML lifecycle basics (data pipelines, model drift, monitoring, inference performance).
• Work with engineers to design and expose AI capabilities via scalable APIs and microservices.

WHAT YOU’LL NEED:

• A Bachelor's/Master's Degree with 5-8 years of Product Management experience, with at least 2–3 years in Agentic AI, Gen AI, AI/ML, data products, or automation-based products.
• Experience working with APIs, microservices, and modern cloud architectures (AWS/Azure/GCP).
• Ability to write detailed requirements for API integrations, data flows, and AI capabilities.
• Strong understanding of ML concepts (classification, NLP/LLMs, predictive models, evaluation metrics).
• Proven ability to work with Data Science and Engineering teams in a deeply technical environment.
• Strong problem-solving skills with a bias for experimentation, iteration, and measurable output.
• Excellent communication skills, especially in simplifying complex AI concepts for non-technical stakeholders.

Preferred Qualifications:

• Experience in InsurTech, Life & Annuities, financial services, or regulated industries.
• Familiarity with underwriting data sources (e.g., Rx, MIB, credit), claims/operations automation, or distribution workflows.
• Experience with LLM products, vector databases, prompt engineering, or RAG systems.
• Exposure to compliance frameworks related to AI ethics, data privacy, and model governance.

WHAT’S IN IT FOR YOU?

Zinnia offers excellent career progression and competitive compensation. We offer great benefits, including health/dental insurance, parental leave, profit sharing, PF, incentive/bonus opportunity, tuition reimbursement, and so much more. We’re looking for the best and brightest innovators in the industry to join our team. At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability.

_#LI-RS1