Machine Learning Ml Engineer
Posted 2 weeks ago by 1752835505
Negotiable
Outside
Remote
USA
Summary: The role of Machine Learning Engineer involves leveraging Generative AI and traditional machine learning to address complex business challenges. The engineer will transition models from concept to production, ensuring they are robust and scalable, while utilizing a tech stack that includes Python and Google Cloud Platform. Responsibilities include developing Generative AI solutions, deploying machine learning models, and collaborating with cross-functional teams to deliver integrated AI/ML solutions. The position requires a strong background in machine learning, programming, and cloud platforms, particularly Google Cloud.
Key Responsibilities:
- Design, develop, and fine-tune Generative AI solutions using models like Gemini.
- Architect and implement advanced Retrieval-Augmented Generation (RAG) systems.
- Research and apply emerging GenAI techniques for autonomous systems.
- Design and deploy a wide range of ML models on Google Cloud Platform.
- Build and maintain automated MLOps pipelines for data preprocessing and model deployment.
- Conduct deep data analysis to guide feature engineering and improve model performance.
- Collaborate with data scientists and software engineers to define technical requirements.
- Champion best practices in software engineering and MLOps.
- Continuously evaluate advancements in the ML and GenAI landscape.
Key Skills:
- 3+ years of experience in building and deploying machine learning models.
- Bachelor's degree in Computer Science, Data Science, Statistics, or related field.
- Advanced proficiency in Python and core data science/ML libraries.
- Advanced proficiency in SQL for data manipulation and analysis.
- Hands-on experience in prompt engineering and fine-tuning Large Language Models.
- Experience with Google Cloud Platform.
- Solid understanding of MLOps principles and related tools.
- Master's or PhD in a relevant field (preferred).
- Experience building RAG systems (preferred).
- Proven ability to lead technical projects and mentor engineers (preferred).
Salary (Rate): undetermined
City: undetermined
Country: USA
Working Arrangements: remote
IR35 Status: outside IR35
Seniority Level: undetermined
Industry: IT
The Opportunity
We are seeking a talented and experienced Machine Learning Engineer. In this role, you will be at the forefront of applying Generative AI and traditional machine learning to solve complex business challenges.
You will bridge the gap between data science and software engineering, taking models from concept to production and ensuring they are robust, scalable, and impactful.
You'll work with a modern tech stack centered on Python, Google Cloud Platform, and the latest in LLM technology.
Generative AI Development:
-Design, develop, and fine-tune Generative AI solutions using models like Gemini for tasks such as information extraction, document summarization, and report generation.
-Architect and implement advanced Retrieval-Augmented Generation (RAG) systems to enhance model accuracy and provide verifiable, context-aware responses.
-Research and apply emerging GenAI techniques, such as agentic frameworks, to build more autonomous and capable systems.
End-to-End Machine Learning:
-Design and deploy a wide range of ML models (classification, regression, forecasting, etc.) on Google Cloud Platform.
-Build and maintain robust, automated MLOps pipelines for data preprocessing, feature engineering, model training, validation, and deployment using tools like Vertex AI, BigQuery. etc.
-Conduct deep data analysis to uncover insights, validate hypotheses, and guide feature engineering for improved model performance.
Collaboration & Strategy:
-Partner closely with data scientists, software engineers, and other business stakeholders to frame problem statements, define technical requirements and deliver integrated AI/ML solutions.
-Champion best practices in software engineering and MLOps to ensure the quality, maintainability, and scalability of our machine learning systems.
-Continuously evaluate and stay current with the latest advancements in the ML and GenAI landscape.
Required Qualifications
-Experience: 3+ years of professional experience building and deploying machine learning models in a production environment.
-Education: Bachelor's degree in Computer Science, Data Science, Statistics, or a related quantitative field.
-Programming: Advanced proficiency in Python and its core data science/ML libraries (e.g., PyTorch, scikit-learn, Pandas).
-Data & SQL: Advanced proficiency in SQL for complex data manipulation, aggregation, and analysis.
-Generative AI: Demonstrable, hands-on experience in prompt engineering and/or fine-tuning Large Language Models (e.g., Gemini).
-Cloud Platform: Hands-on experience with a major cloud provider, with a strong preference for Google Cloud Platform.
-MLOps: Solid understanding of MLOps principles and experience with related tools (e.g., Vertex AI, CI/CD).
Preferred Qualifications (Nice-to-Haves):
-Master s or PhD in a relevant field.
-Specific experience with Google Cloud Platform services like Vertex AI, BigQuery, Storage, and GKE.
-Experience building RAG systems from the ground up.
-Proven ability to lead technical projects and mentor other engineers