AI/ML Data Scientist - MLOps, Quantitative, Statistics

AIToolboard; Washington (District of Columbia); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

W2 benefits

Medical, Dental, Vision

PTO 21 days

401k

Tuition reimbursement

Performance bonuses

Paid overtime

Job summary

Systems Engineering Services in Washington, DC is seeking a Senior AI/ML Engineer/Data Scientist with MLOps experience to build production-grade AI/ML solutions end-to-end. This role requires translating business problems into robust ML systems and delivering scalable, reliable models.

You will develop models, deploy pipelines, and collaborate with MLOps teams to monitor, version, and retrain models for production use. Strong software engineering and communication skills are essential.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field.

Responsibilities

• Translate complex business requirements into AI/ML-based technical solutions and ensure efficiency, scalability and reliability.
• Design, develop, validate, and document AI/ML models and applications.
• Build production-grade Python code and pipelines for data processing, feature engineering, training, and inference.
• Develop model-driven applications and services (batch or real-time).
• Apply software engineering best practices including modular design, testing, code reviews, and CI/CD.
• Collaborate with MLOps teams on deployment, monitoring, versioning, and retraining.
• Implement model performance, stability, and data drift monitoring.
• Produce documentation to support governance, validation, and audit requirements.

Skills

Python

Statistical modeling

ML/AI platforms

MLOps

Data processing

Education

BSc/MSc in DS

Tools

TensorFlow

PySpark

SageMaker

MLflow

Redshift

Job description

Jobs / AI/ML Data Scientist - MLOps, Quantitative, Statistics

AI/ML Data Scientist - MLOps, Quantitative, Statistics

Full-time

About the Role

Sr AI/ML Engineer with Data Scientist and MLOps experienceType: W2 With Benefits - No C2CLocation: Hybrid 2-3 days onsite in Washington, DCTop 5 Technical Skills

Top 5 Technical Skills

• Statistical modeling, machine learning, AI, and applied analytics
• Python
• AWS ML Platforms (AWS SageMaker, MLFlow, S3, compute services, Redshift)
• Model deployment and MLOps practices
• Data Processing

Job Description

We are seeking a Full Stack Data Scientist to develop AI/ML solutions end-to-end, from business problem formulation and model development through production-ready application delivery and operationalization. This role combines deep modeling expertise, strong software engineering skills, and practical MLOps experience. The ideal candidate builds models that matter, writes code that lasts, and partners with platform teams to deploy, monitor, and operate AI/ML solutions efficiently and reliably at scale.

Key Responsibilities

• Translate complex business requirements into AI/ML-based technical solutions and ensure efficiency, scalability and reliability
• Design, develop, validate, and document AI/ML models and applications
• Build production-grade Python code and pipelines for data processing, feature engineering, training, and inference.
• Develop model-driven applications and services (batch or real-time).
• Apply software engineering best practices including modular design, testing, code reviews, and CI/CD.
• Collaborate with MLOps teams on deployment, monitoring, versioning, and retraining.
• Implement model performance, stability, and data drift monitoring.
• Produce documentation to support governance, validation, and audit requirements.

Required Qualifications

• Proven hands-on experience (6+ years preferred) in production-ready models and applications that solve real business problems while actively participating in MLOps to ensure solutions operate reliably in production.
• Strong experience in statistical modeling, machine learning, AI, and applied analytics.
• Advanced proficiency in Python, ML libraries, SQL, and big data processing (e.g. pandas, NumPy, scikit-learn, TensorFlow, PySpark ).
• Experience writing production-ready, maintainable code and application design.
• Strong experience with AWS cloud ML platforms (e.g., AWS SageMaker, MLFlow, S3, compute services, Redshift).
• Experience with model deployment and MLOps practices
• Strong problem-solving and communication skills.

Education

Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field.

Benefits:SES hires W2 benefitted and non-benefitted consultants. Our contract employee benefits include group medical dental vision life LT and ST disability insurance, 21 days of accrued paid time off, 401k, tuition reimbursement, performance bonuses, paid overtime, and more.

Please contact me to discuss the details of this position further.

Please forward resume directly to for immediate consideration - rstarinieri at sesc .com

I look forward to speaking with you soon!Robin StarinieriDirector of RecruitingSystems Engineering Services