Minimum Qualifications – Education & Prior Job Experience
- Master or PhD degree with 5+ years of experience in quantitative discipline preferred (e.g., Data Science, Machine Learning Engineer, Computer Science, Applied Mathematics, Statistics, etc.)
- Python proficiency (production-grade coding, modularization, testing, performance tuning)
- Hands on experience with building Gen AI applications – prompt engineering, classifiers, knowledge bases, RAG solutions, LLMs as judges, etc.
- Hands-on experience with ML/AI pipeline development and productionization (model deployment, orchestration, monitoring, and optimization)
- Depth of knowledge in statistical and machine learning techniques
Preferred qualifications – Education & Prior Job Experience
- Experience with Azure ML, Databricks
- Proficiency in SQL and working with data
- Experience with ML lifecycle tools (e.g., MLflow, CI/CD, model monitoring)
- Practical experience designing, building and deploying machine learning models
- Domain knowledge in the airline industry
- Experience working in a consulting role
- 5-7 years of experience required
Skills, Licenses & Certifications
- Ability to effectively communicate both verbally and written with all levels within the organization
- Demonstrated motivation and aptitude for logical analysis, problem identification, and problem solving
- Ability to view data from different angles to employ feature engineering techniques to better represent models
- Ability to work on a diverse team with diverse skillsets
Top 3 Mandatory Skills and Experience:
- Proficient in Python
- Experience/knowledge on designing and implementing Gen AI applications
- Hands-on experience with Machine Learning and AI pipeline build, model deployment, orchestration, monitoring, and optimization
Nice to Have Skills:
- Microsoft Dynamics
- Prompt Engineering
- Proficiency in SQL and working with data
- Experience with ML lifecycle tools (e.g., MLflow, CI/CD, model monitoring)
- Describe a great candidate that you are looking for and what skills and experience they will have:
- Has experience with LLMs and Agentic AI
- Has experience building customer facing Gen AI applications; awareness on guardrails, privacy, cybersecurity concerns
- Has proven experience taking ML models from prototype to production with Python and Azure ML; containerize where needed.
- Demonstrated strong skills in code optimization, debugging, and system integration.
- Understands end-to-end ML lifecycle, including deployment and monitoring.
- Is comfortable working with existing codebases and improving them, as well as building new ones from scratch. Clear communication and effective collaboration.
Why Join Us?
- 401(k) Matching Plan
- Relationship Driven Process to Find Your Best Fit
- 6 Paid Holidays
- Regular Meetings to Ensure Quality in Your Engagement
EEO Statement:
Brooksource is an equal opportunity employer that does not discriminate on the basis of actual or perceived race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression, sexual orientation, marital status, military service and veteran status, physical or mental disability, protected medical condition as defined by applicable state or local law, genetic information, or any other characteristic protected by applicable federal, state, or local laws and ordinances.
Brooksource offers competitive medical, dental, vision, Health Savings Account, Dependent Care FSA, and supplemental coverage with plans that can fit each employee’s needs. We offer a 401k plan that includes a company match and is fully vested after you become eligible, paid time off, sick time, and paid company holidays. We also offer an Employee Assistance Program (EAP) that provides services like virtual counseling, financial services, legal services, life coaching, etc.
Pay Disclaimer:
The pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
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