Engineering Manager (Search And Match)

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-