TWG Global ยท 2 months ago
Principal Machine Learning Engineer
New York, NY
Full-time
Hybrid
Lead/Staff
$275K/yr - $375K/yr
8+ years expTWG Global is focused on driving innovation and business transformation across various industries by leveraging data and AI. As a Principal Machine Learning Engineer, you will play a critical role in accelerating the delivery of AI solutions by collaborating with Data Scientists and transforming prototypes into production-ready services.
Construction
Responsibilities
Translate data science prototypes into production-ready pilot ML services tailored to business use cases
Build lightweight pipelines (feature engineering, model packaging, inference services) that integrate smoothly with central platforms while meeting immediate delivery needs
Champion pragmatic MLOps practices (CI/CD for ML, monitoring, observability) to improve reliability without duplicating central engineering's enterprise frameworks
Partner closely with Data Scientists to operationalize models, and collaborate with central engineering to plan handoffs of successful pilots for hardening and scale
Apply emerging ML engineering techniques (LLM deployment, RAG, vector databases) to accelerate delivery of applied projects
Develop reusable components and lessons learned that central teams can adopt into firm-wide platforms
Ensure ML workflows comply with governance, audit, and regulatory requirements
Collaborate with central Engineering, Data, Product, and Security teams to ensure alignment with firm-wide platforms and standards
Provide technical mentorship to ML engineers, raising the bar for applied delivery and model deployment
Flex into data science tasks when needed: feature engineering, model experimentation, and analytical insights, reflecting the versatility required in a fast-moving team
Qualification
Required
8+ years of experience designing, building, and deploying ML systems in production
Proven track record of leading ML engineering projects from prototype to production delivery
Deep expertise in modern ML frameworks (TensorFlow, PyTorch, JAX, Ray, MLflow, Kubeflow)
Proficiency in Python and at least one backend language (e.g., Java, Scala, Go, C++)
Strong knowledge of cloud ML infrastructure (AWS SageMaker, GCP Vertex AI, Azure ML) and containerized deployments (Kubernetes, Docker)
Hands-on experience with ML pipelines, distributed training, and inference scaling
Familiarity with monitoring stacks (Prometheus, Grafana, ELK, Datadog)
Experience in regulated industries (finance, insurance, healthcare) with compliance and governance needs
Strong communication and collaboration skills, with the ability to mentor others and influence technical direction
Working knowledge of data science techniques (e.g., supervised/unsupervised ML, model evaluation, causal inference, feature engineering)
Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related technical field (PhD a plus)
Preferred
Experience integrating with Palantir platforms (Foundry, AIP, Ontology) as a user/consumer
Practical exposure to LLM and GenAI delivery (fine-tuning, RAG, vector search, inference)
Experience optimizing GPU clusters or distributed training workloads
Familiarity with graph databases (Neo4j, TigerGraph) in applied ML contexts
Benefits
A discretionary bonus will be provided as part of the compensation package
A full range of medical, financial, and/or other benefits
Company
TWG Global
TWG Global is a unique holding company, strategically investing in and operating businesses across Investment Management, Securities, AI & Technology, Finance & Corporate Lending, Merchant Banking & Private Investments, and Sports, Media & Entertainment.
51-200 employees
Funding
Current Stage
Growth StageCompany data provided by crunchbase