ML Engineer

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.