Sr. Machine Learning Operations Engineer

Software Guidance & Assistance, Inc., (SGA), is searching for a Sr. Machine Learning Operations Engineer (MLOps) for a Contract assignment with one of our premier Financial Services clients in New York, NY. The Manager is also open to 100% Remote!

We are looking for a a Sr. Level Machine Learning Operations Engineer to help lead MLOps strategy and solutions. This role will help lead, implement and define the MLOps, LLMOps technology and platform strategy, and design and develop AI/ML/LLM/GAI technology platforms while working with a broad range of partners across data, technology and business teams. In this role, you will play a pivotal role in helping lead and implementing our machine learning strategy and operations, ensuring the seamless deployment, monitoring, and management of our machine learning models and data pipelines. You will help lead ML infrastructure initiatives, mentor junior team members, and contribute to the strategic direction of our MLOps infrastructure. You will be instrumental in leading strategic direction for ML infrastructure in a world class AI ML team while working alongside well-known experts and researchers in AI ML modeling, ML engineers and data science and data engineering teams. You will contribute to setting roadmaps for AI operations and be a critical part of leading AI-driven transformation to drive value internally and for our customers.

Responsibilities :

• MLOps Strategy: Develop and implement MLOps strategies, best practices, and standards to enhance AI ML model deployment and monitoring efficiency. Develop roadmap and strategy for MLOps and LLMOps Platforms and model lifecycle implementation
• ML Architecture Design and Development: Responsible for the design and development of custom architecture for batch and stream processing-based AI ML pipelines including data ingestion to preprocessing to scaled AI model compute and ensure the architecture meets all SLA requirements. Work closely with members of technology and business teams in the design, development, and implementation of Enterprise AI platform.
• Infrastructure Management: Oversee the design, deployment, and management of scalable and reliable infrastructure for AI, ML , GenAI, LLM model training and deployment.
• Model Deployment: Lead the deployment of GenAI, LLM , machine learning models into production environments, ensuring reliability and scalability.
• Monitoring and Optimization: Create and maintain robust monitoring systems to track model performance, data quality, and infrastructure health.
• Identify and implement optimizations to improve system efficiency.
• Automation: Develop and maintain automated pipelines for model training, testing, and deployment, optimizing for speed and reliability. Ensure CI-CD best practices are followed.
• Internal Collaboration: Collaborate closely with data scientists, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems.
• Stakeholder Engagement and Collaboration: Collaborate closely with business and PM stakeholders in roadmap planning and implementation efforts and ensure technical milestones align with business requirements.
• Security and Compliance: Implement security measures and compliance standards to protect sensitive data and ensure adherence to industry regulations.
• Mentorship: Recruit, develop and mentor technical AI/ML engineering talent on the team
• Provide guidance and mentorship to junior MLOps engineers, fostering their professional growth and development.
• Documentation: Maintain comprehensive documentation of MLOps processes and procedures for reference and knowledge sharing.
• Standards and Best Practices: Ensure the use of standards, governance and best practices in ML pipeline monitoring and ML model monitoring, and adherence to model and data governance standards
• Problem Solving: Troubleshoot complex issues related to machine learning model deployments and data pipelines, and develop innovative solutions.

Required Skills:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Experienced professional (7+ years experience) as ML engineer, architect, engineer, lead data scientist in Big Data ecosystem or any similar distributed or public cloud platform, with a desire to assume greater responsibilities as a leader and mentor, while still being hands-on.
• 4+ years hands-on experience in integrating, evaluating, deploying, operationalizing ML and LLM models at speed and scale, including integration with enterprise applications and APIs. (In addition, ideal candidate should also have hands on experience on training and fine-tuning ML and LLM models at scale)
• Expertise (4+ years) in distributed computing and orchestration technology (Kubernetes, Ray, Airflow) and scaling
• Experience with public cloud platform & systems (AWS, GCP, Azure)
• Proficiency with Databricks, MLflow, Flink, GPT4All, Kore.ai, or similar AI/ML/ML Ops technologies
• Experience developing with SQL, NoSQL, ElasticSearch, MongoDB, and Spark, Python, PySpark for model development and ML Ops
• Knowledge of DevOps, MlOps principles and practices, and experience with version control systems (e.g., Git) and CI/CD pipelines.
• Excellent written & verbal communication and stakeholder management skills
• Strategic thinker and influencer with demonstrated technical and business acumen and problem-solving skills
• Experienced with LLMs (extractive and generative), fine-tuning and operationalizing LLM pipelines.
• Strong familiarity with higher level trends in LLMs and open-source platforms
• Nice to have: Experience with contributing to Github and open source initiatives or in research projects

SGA is a technology and resource solutions provider driven to stand out. We are a women-owned business. Our mission: to solve big IT problems with a more personal, boutique approach. Each year, we match consultants like you to more than 1,000 engagements. When we say let's work better together, we mean it. You'll join a diverse team built on these core values: customer service, employee development, and quality and integrity in everything we do. Be yourself, love what you do and find your passion at work. Please find us at https://sgainc.com/ .

SGA is an Equal Opportunity Employer and does not discriminate on the basis of Race, Color, Sex, Sexual Orientation, Gender Identity, Religion, National Origin, Disability, Veteran Status, Age, Marital Status, Pregnancy, Genetic Information, or Other Legally Protected Status. We are committed to providing access, equal opportunity, and reasonable accommodation for individuals with disabilities in employment, and our services, programs, and activities. Please visit our company EEO page to request an accommodation or assistance regarding our policy. •

Last updated on Nov 9, 2023