Dexian
Overview
We are seeking an experienced AI/ML Engineer to design, develop, train, and deploy machine learning solutions addressing real-world business challenges. The ideal candidate is proficient with Databricks within the Azure ecosystem, demonstrating expertise in Spark, Delta Lake, and MLflow. You will own all phases of the machine learning lifecycle—from data exploration and feature engineering to model training, validation, deployment, and monitoring—while collaborating with cross-functional teams to drive measurable impact through AI. This position is based in Seffner, FL, with a hybrid work arrangement and opportunities for professional growth in a supportive, learning-driven environment. Responsibilities
Perform exploratory data analysis, feature engineering, and data preprocessing using Python and SQL within Databricks Notebooks. Build, train, and maintain machine learning models using Databricks and integrate with Azure services as needed. Leverage MLflow for experiment tracking, model versioning, registration, and deployment. Deploy and monitor models across development, testing, and staging environments using Databricks Model Serving. Apply MLOps principles to ensure reproducibility, scalability, and maintainability throughout the ML lifecycle. Collaborate with data engineers to ensure data quality and availability, and with BI developers to embed predictive insights into Power BI dashboards. Conduct requirements gathering and solution design discussions with business stakeholders. Apply emerging prompt engineering techniques (e.g., chain-of-thought, tree-of-thought, prompt chaining) to enhance LLM-based use cases. Document code, workflows, and experiments clearly and consistently. Participate in Agile sprint meetings, proactively report progress, and engage in peer reviews and mentorship sessions. Qualifications
Education Bachelor’s degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a related quantitative field preferred. Certifications such as Databricks AI Engineering Associate, Databricks ML Engineering Associate, or Azure AI Engineer Associate are highly desirable. Experience 2–4 years of hands-on experience developing and deploying AI/ML models using Python. Proven experience working within a cloud environment (preferably Azure; AWS/GCP acceptable). Strong background in Databricks for data processing and machine learning. Practical understanding of software engineering best practices and version control (Git). Technical Skills Languages & Tools: Python, SQL, Git Databases: Azure SQL, Delta Tables, or other relational data stores Cloud Platforms: Azure (preferred), AWS, or GCP Libraries: scikit-learn, pandas, NumPy, matplotlib/seaborn Familiarity with LLMs, generative AI, and emerging agentic AI concepts is a plus. Strong analytical and problem-solving skills with high attention to detail. Clear communication skills (verbal and written) with the ability to collaborate across teams. Self-starter who can work independently on moderately complex projects. Organized and capable of managing multiple concurrent tasks effectively. Growth-oriented mindset, eager to learn and adopt new AI/ML tools and practices. Seniority level
Mid-Senior level Employment type
Full-time Job function
Information Technology Industries Retail Referrals increase your chances of interviewing at Dexian by 2x
#J-18808-Ljbffr
We are seeking an experienced AI/ML Engineer to design, develop, train, and deploy machine learning solutions addressing real-world business challenges. The ideal candidate is proficient with Databricks within the Azure ecosystem, demonstrating expertise in Spark, Delta Lake, and MLflow. You will own all phases of the machine learning lifecycle—from data exploration and feature engineering to model training, validation, deployment, and monitoring—while collaborating with cross-functional teams to drive measurable impact through AI. This position is based in Seffner, FL, with a hybrid work arrangement and opportunities for professional growth in a supportive, learning-driven environment. Responsibilities
Perform exploratory data analysis, feature engineering, and data preprocessing using Python and SQL within Databricks Notebooks. Build, train, and maintain machine learning models using Databricks and integrate with Azure services as needed. Leverage MLflow for experiment tracking, model versioning, registration, and deployment. Deploy and monitor models across development, testing, and staging environments using Databricks Model Serving. Apply MLOps principles to ensure reproducibility, scalability, and maintainability throughout the ML lifecycle. Collaborate with data engineers to ensure data quality and availability, and with BI developers to embed predictive insights into Power BI dashboards. Conduct requirements gathering and solution design discussions with business stakeholders. Apply emerging prompt engineering techniques (e.g., chain-of-thought, tree-of-thought, prompt chaining) to enhance LLM-based use cases. Document code, workflows, and experiments clearly and consistently. Participate in Agile sprint meetings, proactively report progress, and engage in peer reviews and mentorship sessions. Qualifications
Education Bachelor’s degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a related quantitative field preferred. Certifications such as Databricks AI Engineering Associate, Databricks ML Engineering Associate, or Azure AI Engineer Associate are highly desirable. Experience 2–4 years of hands-on experience developing and deploying AI/ML models using Python. Proven experience working within a cloud environment (preferably Azure; AWS/GCP acceptable). Strong background in Databricks for data processing and machine learning. Practical understanding of software engineering best practices and version control (Git). Technical Skills Languages & Tools: Python, SQL, Git Databases: Azure SQL, Delta Tables, or other relational data stores Cloud Platforms: Azure (preferred), AWS, or GCP Libraries: scikit-learn, pandas, NumPy, matplotlib/seaborn Familiarity with LLMs, generative AI, and emerging agentic AI concepts is a plus. Strong analytical and problem-solving skills with high attention to detail. Clear communication skills (verbal and written) with the ability to collaborate across teams. Self-starter who can work independently on moderately complex projects. Organized and capable of managing multiple concurrent tasks effectively. Growth-oriented mindset, eager to learn and adopt new AI/ML tools and practices. Seniority level
Mid-Senior level Employment type
Full-time Job function
Information Technology Industries Retail Referrals increase your chances of interviewing at Dexian by 2x
#J-18808-Ljbffr