Data Science Engineer (AI)

TL;DR

Data Science Engineer (AI): Building and scaling data-driven products and services by transforming raw data into actionable intelligence, developing and deploying robust machine learning models. Focus on establishing foundational MLOps workflows on modern cloud infrastructure and refining prompt engineering for model fine-tuning and augmentation.

Location: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor, or take over sponsorship of an employment Visa at this time.

Salary: $90,000–$120,000

Company

hirify.global is a software development company specializing in agile software development, cloud professional services, and innovative product creation, recognized as a Great Place to Work.

What you will do

• Design and implement scalable data pipelines to ingest, process, and transform large datasets.
• Develop, validate, and optimize supervised and unsupervised machine learning models leveraging Python and SQL.
• Build and expose model APIs or containerized workflows for seamless integration and deployment in production.
• Apply MLOps best practices to model versioning, testing, monitoring, and deployment.
• Work with Big Data technologies like Databricks and Snowflake, and orchestrate complex workflows using Airflow or Dagster.
• Collaborate with AI teams to refine prompt engineering and leverage AI tooling for model fine-tuning and augmentation, utilizing leading cloud platforms (AWS, Azure, GCP).

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics, or a related field.
• 3+ years of experience in data science engineering or related roles.
• Proficiency in Python and SQL for data extraction, analysis, and modeling.
• Strong background in statistical modeling and machine learning algorithms, with experience in feature engineering and end-to-end model development.
• Hands-on experience with MLOps foundations (CI/CD, model monitoring, automated retraining).
• Familiarity with Big Data tools (Databricks, Snowflake, Spark) and workflow orchestration platforms (Airflow or Dagster).
• Understanding of cloud architecture and deployment (AWS, Azure, GCP), and experience deploying models as APIs or containers (Docker, FastAPI, Flask).
• Familiarity with prompt engineering techniques and AI tooling.
• Applicants must be authorized to work for ANY employer in the U.S.

Nice to have

• Experience with advanced AI tools (e.g., LLMs, vector databases).
• Exposure to data visualization tools and dashboarding.
• Knowledge of security, privacy, and compliance in ML workflows.

Culture & Benefits

• Comprehensive health, dental, and vision insurance.
• 401k retirement savings plan with company match (pre-tax and ROTH options).
• Flexible time off, paid holidays, and employer-paid disability and life insurance.
• Employee assistance program, flexible spending accounts, and health savings account with employer contributions.
• Professional development opportunities including leadership training and Udemy online training courses.
• Tickets to local sporting events and teambuilding events.