Machine Learning Engineer
BayOne Solutions I Multiple Global Locations (Remote)
Position Overview
BayOne Solutions is seeking an exceptional Senior Machine Learning Engineer who combines strong programming fundamentals with practical machine learning expertise and proven ability to deploy ML systems in production environments. This role is critical to building robust, scalable machine learning solutions while serving as a technical mentor and strategic contributor to our AI initiatives.
As our Senior Machine Learning Engineer, you will architect and implement traditional ML systems, guide technical decision-making between classical ML and generative AI approaches, and work collaboratively across our GenAI, computer vision, and web development teams. This position offers the opportunity to work with Fortune 500 clients while building production ML systems that solve real business challenges.
Key Responsibilities
Machine Learning Development & Implementation (40%)
Design and implement end-to-end ML pipelines for recommendation systems, search ranking, and classification problems
Build and optimize traditional ML models using techniques such as ensemble methods, SVMs, gradient boosting, and neural networks
Develop time series forecasting models and ranking algorithms for complex business applications
Implement feature engineering pipelines that handle real-world data noise and edge cases
Create robust data preprocessing and validation systems that ensure model reliability in production
Production ML Systems & Deployment (25%)
Deploy ML models using Docker containerization and REST API frameworks (Flask/FastAPl)
Implement model serving solutions on Azure Container Instances with proper monitoring and
alerting
Build MLOps pipelines using MLflow for experiment tracking and model registry management
Design scalable data workflows using Apache Airflow and Azure Data Factory for ETL operations
Establish model versioning, rollback strategies, and performance monitoring in production environments
Technical Leadership & Collaboration (20 O )
Serve as a technical sounding board for AI team members on ML architecture and approach decisions
Mentor team members on best practices for production ML system design and implementation
Communicate complex technical concepts clearly to both technical and non-technical stakeholders
Collaborate across AI, web development, and system architecture teams to ensure seamless integration
Guide strategic decisions on when to use traditional ML versus generative AI approaches
Strategic ML Decision Making (15%)
Evaluate problems to determine optimal solutions: classical ML, GenAI, or simpler analytical methods
Integrate generative AI tools effectively into workflows without over-relying on them
Design ML systems that integrate seamlessly with existing web application architectures
Provide technical guidance on model selection, evaluation metrics, and performance optimization
Stay current with ML best practices while maintaining focus on practical, business-driven solutions
Required Qualifications
Education & Experience
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related technical field
4+ years of hands-on experience building and deploying machine learning systems in production
Proven experience working in non-technical business domains (healthcare, finance, retail, HR, etc.)
Track record of mentoring technical team members and leading collaborative projects
Core Technical Skills
Programming Excellence: Expert-level Python proficiency with focus on clean, maintainable, production-ready code
Traditional ML Expertise: Deep understanding of classification, regression, ranking, and recommendation algorithms
Production ML: Experience with MLOps practices, model deployment, monitoring, and lifecycle management
Data Engineering: Proficiency with data pipeline development, ETL processes, and handling messy real-world datasets
Cloud Platforms: Hands-on experience with Azure ML Studio, Azure Container Instances, and Azure Data Factory
Specialized Experience
Experience building recommendation engines, search ranking systems, or time series forecasting
models
Background in A/B testing methodologies and measuring business impact of ML initiatives
Knowledge of feature stores, model registry systems, and ML experiment tracking
Understanding of model interpretability, bias detection, and fairness in ML systems
Experience with both structured and unstructured data processing at scale
Experience with deep learning frameworks (TensorFlow, PyTorch) for appropriate use cases
Communication & Leadership
Excellent verbal and written communication skills with ability to explain complex concepts clearly
Proven ability to work effectively across technical and business teams
Experience mentoring junior developers while maintaining strong individual contribution
Track record of proactive collaboration and knowledge sharing in team environments
Excellent problem-solving capabilities with ability to approach complex challenges systematically
Self-motivated with strong ability to plan and architect technical solutions independently
Preferred Qualifications
Knowledge of natural language processing techniques and text classification systems
Background in building ML systems for talent acquisition, recruiting, or HR technology
Experience with real-time ML inference and low-latency model serving
Understanding of distributed computing and large-scale data processing
About Bayone Solutions
BayOne Solutions is a minority-owned Technology and Talent Solutions Partner that has appeared on the Inc. 5000 list four times and the San Francisco Business Times Fast 100 list five times. We are committed to diversity, innovation, and building human-centric technology solutions that empower businesses and individuals alike.
Our technology initiatives represent significant investment in AI and machine learning platforms, positioning us as a leader in delivering intelligent solutions for Fortune 500 clients.
Application Process
We are looking for candidates who can demonstrate both technical excellence and collaborative leadership. Please submit your resume along with examples of machine learning systems you've built and deployed, particularly those showing:
Production ML pipelines you've architected and implemented
Examples of choosing appropriate ML approaches for specific business problems
Evidence of mentorship or technical leadership experience
Equal Opportunity Employer: BayOne Solutions is committed to creating a diverse and inclusive workplace and is proud to be an equal opportunity employer.
This position o[fers an exceptional opportunity to lead machine learning innovation while building production systems that solve real business challenges in a collaborative, cross-[unctional environment.