Gen AI & ML Scientist – Hybrid, Fort Worth

Saksoft; Fort Worth (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Saksoft is hiring a Data Scientist to join our Fort Worth, TX team onsite 3 days a week (Tue–Thu), with Monday/Friday as virtual. The role requires 5+ years in quantitative fields, strong Python skills, and hands-on Gen AI experience.

Preference for Azure ML, Databricks, MLflow, CI/CD, and airline-domain knowledge. The position involves building ML pipelines, deploying models, and monitoring performance in production, with collaboration across business units and client projects.

Qualifications

• Master or PhD degree in a quantitative discipline with 5 years of experience
• Proficient in Python with production-grade coding practices
• Hands on experience with Gen AI applications — prompt engineering, classifiers, knowledge bases, RAG, LLMs as judges
• Experience building ML/AI pipelines and productionizing models (deployment, orchestration, monitoring, optimization)
• Strong knowledge of statistical and machine learning techniques
• Experience with Azure ML, Databricks; SQL proficiency; ML lifecycle tools (MLflow, CI/CD, monitoring)
• Experience designing, building and deploying ML models; consulting experience and airline domain knowledge are a plus
• Excellent verbal and written communication; ability to work with diverse teams

Skills

Python

Gen AI applications

ML pipeline

Model deployment

Orchestration

Monitoring

Optimization

Statistical ML

SQL

Communication skills

Feature engineering

Team collaboration

Analytical thinking

Airline domain knowledge

Consulting experience

Education

Master or PhD degree

Tools

Azure ML

Databricks

MLflow

CI/CD

Model monitoring

Job description

Saksoft is hiring a Data Scientist to join our Fort Worth, TX team onsite 3 days a week (Tue–Thu), with Monday/Friday as virtual. The role requires 5+ years in quantitative fields, strong Python skills, and hands-on Gen AI experience.

Preference for Azure ML, Databricks, MLflow, CI/CD, and airline-domain knowledge. The position involves building ML pipelines, deploying models, and monitoring performance in production, with collaboration across business units and client projects.