The Role
Lead design, build, and production-deployable ML/Generative AI solutions (RAG, prompt engineering, fine-tuning). Mentor ML teams, implement end-to-end data pipelines, evaluate/tune models, and deliver scalable cloud-based ML systems.
Summary Generated by Built In
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, model evaluation, and inference serving.
● Proven experience building and deploying machine learning models in production environments for real life applications
● Good understanding of natural language processing, computer vision or other deep learning techniques.
● Expertise in Python, Numpy, Pandas and various ML libraries (e.g., XGboost, TensorFlow, PyTorch, Scikit-learn, LangChain).
● Familiarity with Google Cloud or any other Cloud Platform and its machine learning services.
● Excellent communication, collaboration, and problem-solving skills.
● 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, model evaluation, and inference serving.
● Proven experience building and deploying machine learning models in production environments for real life applications
● Good understanding of natural language processing, computer vision or other deep learning techniques.
● Expertise in Python, Numpy, Pandas and various ML libraries (e.g., XGboost, TensorFlow, PyTorch, Scikit-learn, LangChain).
● Familiarity with Google Cloud or any other Cloud Platform and its machine learning services.
● Excellent communication, collaboration, and problem-solving skills.
Good to Have
● Google Cloud Certified Professional Machine Learning or TensorFlow Certified Developer certifications or equivalent.
● Experience of working with one or more public cloud platforms - namely GCP, AWS or Azure.
● Experience with AutoML and vision techniques.
● Master’s degree in statistics, machine learning or related fields.
Skills Required
- At least 5 years experience designing and building ML/AI applications and deploying them to production
- At least 8 years software engineering experience building secure, scalable, performant applications
- At least 2 years leading and mentoring ML/data science teams (4+ team members)
- Experience with document extraction using AI, conversational AI, Vision AI, NLP, or Generative AI
- Design, develop, and operationalize ML models via fine-tuning and personalization
- Evaluate machine learning models and perform necessary tuning
- Develop prompts to instruct LLMs and iteratively improve LLM responses
- Collaborate with data scientists/engineers to analyze and preprocess datasets for prompt development
- Lead design and architecture of scalable, reliable, cost-effective Generative AI solutions (RAG, agentic workflows, fine-tuning)
- Hands-on customer experience with RAG solutions or fine-tuning LLM models
- Build and deploy scalable machine learning pipelines on GCP or equivalent cloud platforms integrating data warehouses, ML platforms, dashboards or CRM tools
- End-to-end ML workflow experience: data cleaning, EDA, outlier handling, balancing, feature engineering, model selection, training and deployment
- Act as senior developer writing clean, high-quality, scalable code for prompt engineering, vector search, data processing, model evaluation, and inference serving
- Proven experience building and deploying ML models in production for real-world applications
- Good understanding of NLP, computer vision, or other deep learning techniques
- Expertise in Python, NumPy, Pandas and ML libraries (XGBoost, TensorFlow, PyTorch, scikit-learn, LangChain)
- Familiarity with Google Cloud or other cloud platforms and their ML services
- Excellent communication, collaboration, and problem-solving skills
- Google Cloud Professional ML or TensorFlow Certified Developer (or equivalent)
- Experience with one or more public cloud platforms (GCP, AWS, Azure)
- Experience with AutoML and vision techniques
- Master's degree in statistics, machine learning, or related field
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The Company
What We Do
Egen is a data engineering and cloud modernization firm partnering with leading Chicagoland companies to launch, scale, and modernize industry-changing technologies. We are catalysts for change who create digital breakthroughs at warp speed. Our team of cloud and data engineering experts are trusted by top clients in pursuit of the extraordinary. Our mission is to be an enabler of amazing possibilities for companies looking to use the power of cloud and data. We want to stand shoulder to shoulder with clients, as true technology partners, and make sure they succeed at what they have set out to do. We want to be disruptors, game-changers, and innovators who have played an important part in moving the world forward.
