Company
Technology
EngineeringManager-AI/ML
Neural analysis suggests this role is
optimal for Manager candidates.
“Engineering Manager-AI/ML. Skills: AI/ML, Generative AI, Machine Learning Engineering, Prompt Engineering. Design ML/AI applications. Build ML/AI applications”
Industry & Context.
Problem-solving skills
What They're Looking For.
Must Have
5 years of experience in designing & building ML/AI applications, 8 years of Software engineering experience, 2 years of experience leading and mentoring ML/data science teams, Experience with Document extraction using AI, Experience with Conversational AI, Experience with Vision AI, Experience with NLP, Experience with Gen AI, Hands on customer experience with RAG solution, Hands on customer experience with fine tuning of LLM model, Proven experience building and deploying machine learning models in production
Nice to Have
Google Cloud Certified Professional Machine Learning, TensorFlow Certified Developer certifications, Experience working with GCP, Experience working with AWS, Experience working with Azure, Experience with AutoML, Experience with vision techniques, Master’s degree in statistics, Master’s degree in machine learning
What You'll Do.
Design ML/AI applications
Build ML/AI applications
Deploy ML/AI applications
Lead ML/data science teams
Mentor ML/data science teams
Operationalize ML models
Personalize ML models
Evaluate machine learning models
Tune machine learning models
Develop prompts for LLM
Analyze datasets for prompt development
Preprocess datasets for prompt development
Evaluate LLM responses
Improve LLM performance
Lead end-to-end design of Generative AI solutions
Lead architecture of Generative AI solutions
Design agentic workflows
Design model fine-tuning strategies
Build machine learning pipelines on GCP
Deploy machine learning pipelines on GCP
Perform exploratory data analysis
Analyze data distributions
Transform data into features
Write high-quality code
Build core components for prompt engineering
Build core components for vector search
Build core components for data processing
Build core components for model evaluation
Build core components for inference serving
Build machine learning models in production
Deploy machine learning models in production
How You'll Work.
Team & Collaboration
Collaborate with data scientists; Collaborate with engineers
Full Job Description
## What we're looking for ● At least 5 years of experience in designing & building ML/AI applications for customer and deploying them into production ● At least 8 years of Software engineering experience in building Secure, scalable and performant applications for customers. ● At least 2 years of experience leading and mentoring ML/data science teams( 4+ team members) ● Experience with Document extraction using AI, Conversational AI, Vision AI, NLP or Gen AI. ● Design, develop, and operationalize existing ML models by fine tuning, personalizing it. ● Evaluate machine learning models and perform necessary tuning. ● Develop prompts that instruct LLM to generate relevant and accurate responses. ● Collaborate with data scientists and engineers to analyze and preprocess datasets for prompt development, including data cleaning, transformation, and augmentation. ● Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to improve LLM performance. ● Lead the end-to-end design and architecture of scalable, reliable, and cost-effective Generative AI solutions. This includes designing RAG (Retrieval-Augmented Generation) pipelines, agentic workflows, and model fine-tuning strategies. ● Hands on customer experience with RAG solution or fine tuning of LLM model. ● Build and deploy scalable machine learning pipelines on GCP or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards or CRM tools. ● Experience working with the end-to-end steps involving but not limited to data cleaning, exploratory data analysis, dealing outliers, handling imbalances, analyzing data distributions (univariate, bivariate, multivariate), transforming numerical and categorical data into features, feature selection, model selection, model training and deployment. ● Act as the senior-most developer, writing clean, high-quality, and scalable code. This includes building core components for prompt engineering, vector search, data processing, m
Applying for this Engineering Manager-AI/ML role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Lever
- Lever uses a streamlined one-page form — apply in under 5 minutes.
- LinkedIn import works well; review parsed data before submitting.
- The cover letter field is optional but visible to reviewers — use it to differentiate.
- Referral codes from employees can significantly boost visibility of your application.
ANONYMOUS · UNFILTERED
What do employees actually say about this company?
Real rants from real employees. Read before you apply.