Position Overview:
ShyftLabs is seeking an experienced Senior Machine Learning Engineer to design
and implement ML infrastructure and assess Agentic BI readiness for Fortune 500
enterprise companies. You will build robust MLOps platforms, design scalable ML
pipelines, and provide strategic guidance for implementing autonomous business
intelligence and AI-driven analytics systems.
ShyftLabs is a growing data product company founded in early 2020 and works
primarily with Fortune 500 companies. We deliver digital solutions built to help
accelerate the growth of businesses in various industries, by focusing on
creating value through innovation.
\n
Job Responsibilities:
-
Design and implement MLOps infrastructure using MLflow, Databricks Unity
Catalogue, and AWS managed services
-
Build feature store implementations and ML model versioning strategies using
Databricks and MLflow
-
Assess AI readiness and design roadmaps for Agentic BI implementations
supporting autonomous insights generation
-
Design production ML systems supporting predictive analytics, classification,
and optimization models
-
Implement ML model deployment pipelines with automated training, validation,
and deployment workflows
-
Build model monitoring and performance management systems for production ML
applications
-
Evaluate generative AI infrastructure requirements including semantic layers
and automated analytics workflows
-
Design ML pipeline automation strategies integrating feature engineering,
model training, and deployment processes
-
Implement real-time ML inference patterns supporting business-critical
applications
-
Enterprise MLOps Expertise: Proven experience implementing ML infrastructure
at Fortune 500 scale
-
Agentic BI Assessment: Understanding of autonomous AI systems and ability to
assess organizational readiness for AI-driven business intelligence
-
Production ML Focus: Deep understanding of ML model deployment, monitoring,
and lifecycle management in production environments
-
Strategic Communication: Strong consulting skills to present ML strategies
and AI readiness roadmaps to executive leadership
Basic Qualifications:
- Bachelor's or Master's degree in Computer Science, Machine Learning,
Engineering, or related quantitative field
- 5+ years of experience in ML engineering with Fortune 500 enterprise-scale
implementations
- Expert-level experience with MLflow for model lifecycle management and
experimentation tracking
- Deep hands-on experience with Databricks ML platform including Unity
Catalogue for ML governance
- Proven experience with AWS ML services including SageMaker, model deployment,
and managed ML infrastructure
- Strong background in machine learning algorithms including
supervised/unsupervised learning, ensemble methods, and deep learning
- Experience with generative AI and LLM integration for business intelligence
applications and semantic data modeling requirements
- Knowledge of feature store architectures, ML data management patterns, and
model versioning/automation workflows
Preferred Qualifications
- Experience with Agentic BI frameworks and autonomous analytics systems
- Knowledge of conversational AI and natural language interfaces for business
intelligence
- Understanding of AI governance frameworks and enterprise AI readiness
assessment
- Experience with real-time recommendation systems and live inference pipelines
- Familiarity with financial modeling or pricing optimization ML applications
- Understanding of A/B testing frameworks for ML model evaluation
- Knowledge of ML governance and regulatory compliance requirements
\n
We are proud to offer a competitive salary alongside a strong healthcare
insurance and benefits package. The role is preferably hybrid, with 2 days per
week spent in the office, and flexibility for client engagement needs. We pride
ourselves on the growth of our employees, offering extensive learning and
development resources.
ShyftLabs is an equal-opportunity employer committed to creating a safe, diverse
and inclusive environment. We encourage qualified applicants of all backgrounds
including ethnicity, religion, disability status, gender identity, sexual
orientation, family status, age, nationality, and education levels to apply. If
you are contacted for an interview and require accommodation during the
interviewing process, please let us know.
