Experience with production-grade testing and CI/CD practices
Familiarity with GCP and data/AI system deployment
Responsibilities
Collaborate with stakeholders to determine machine learning needs
Design and develop innovative machine learning models and algorithms
Build and optimize scalable machine learning pipelines and infrastructure
Apply various modeling techniques to develop and evaluate algorithms
Train and retrain machine learning models as necessary
Deploy models into production and conduct algorithm simulations
Monitor and maintain observability for data pipelines and AI services
Benefits
Four-day work week onsite
Morning work schedule
No travel required
Involvement in cutting-edge technologies like AR and VR
Opportunity for hands-on experience with cloud-native infrastructure
Full Job Description
Machine Learning Engineer II
Overview / Summary
We are seeking a Machine Learning Engineer II responsible for designing, building, deploying, and scaling complex machine learning solutions in areas such as computer vision, perception, and localization. This role will also focus on automating and optimizing the end-to-end machine learning model lifecycle using experimental methodologies, statistics, software development, and MLOps practices.
The position will work closely with business and technology stakeholders to develop machine learning models, scalable pipelines, cloud infrastructure, and production-ready AI solutions.
Key Responsibilities
Collaborate with business and technology stakeholders to understand current and future machine learning requirements.
Design and develop innovative machine learning models and software algorithms to solve complex business problems in structured and unstructured environments.
Design, build, maintain, and optimize scalable machine learning pipelines, architecture, and infrastructure.
Apply machine learning and statistical modeling techniques, including decision trees, logistic regression, Bayesian analysis, and other methods, to develop and evaluate algorithms.
Apply machine learning to areas such as virtual reality, augmented reality, object detection, tracking, classification, and terrain mapping.
Train and retrain machine learning models and systems as required.
Deploy machine learning models and algorithms into production and run simulations for algorithm development and testing.
Automate model deployment, training, and retraining using Agile methodology, CI/CD/CT (Continuous Integration, Continuous Deployment, and Continuous Training), and MLOps principles.
Enable model management, versioning, and traceability to support modularity and consistency across environments and models.
Design, develop, test, and deploy knowledge graph solutions using cloud-native data pipelines.
Model and evolve graph entities and relationships as new data sources are onboarded.
Design, build, and operate services that expose graph and event-store data as tools for consumers, including graph queries, event-store queries, and schema discovery.
Define tool contracts, context, and guardrails to support accurate, grounded responses from AI agents.
Support low-latency, secure, and cost-efficient serving for interactive and batch AI workloads.
Monitor and maintain observability for data pipelines and AI services, including data freshness, pipeline health, query latency and cost, tool-call success rates, and answer quality.
Implement SLOs, dashboards, alerting, and tracing while supporting incident response and continuous reliability improvements.
Partner with data engineers and application data source owners to ingest and validate data.
Establish data contracts, schema validation, and data quality checks.
Support data onboarding, mapping to logical data models, and troubleshooting.
Contribute to data governance, cataloging, and lineage.
Required Qualifications
Bachelor's degree.
7+ years of IT experience.
3+ years of development experience.
2+ years of experience in AI and graph engineering.
Experience with at least one coding language or framework.
Strong software engineering experience with Java and Python.
Experience with production-grade testing, CI/CD, and code quality practices.
Experience deploying data and AI systems to production on a GCP-native stack.
Experience with GCP, BigQuery, Python, Java, cloud infrastructure, and artificial intelligence/expert systems.
Experience with cloud technologies including Vertex AI, BigQuery, Dataflow/Apache Beam, Pub/Sub, Cloud Run/GKE, Cloud Storage, and Cloud Build/Artifact Registry.
Experience with graph data modeling and querying, including property graphs and GQL/graph query patterns.
Experience with Vertex AI, including agents, model serving, embeddings, and evaluation of agent answer quality.
Experience building LLM/agent systems, including tool use, RAG/grounding, and integrating models through APIs.
Familiarity with MCP or comparable agent tool protocols.
Experience with observability, including Cloud Monitoring/Logging, OpenTelemetry, SLOs, dashboards, and alerting for data pipelines and services.
Experience with Infrastructure as Code using Terraform.
Experience with secure-by-default engineering practices, including IAM, least privilege, and secrets management.
Ability to work directly with data producers to model and validate real-world industrial or enterprise data.
Preferred Qualifications
Familiarity with Dataplex/Data Catalog for governance, lineage, and business glossaries.
Experience with streaming/CDC and event-driven architectures.
Experience with append-only or event-sourced data modeling.
Experience designing and building user-facing applications and dashboards that surface knowledge graph data.
Domain exposure to PLM/product development, manufacturing execution, quality, or supply-chain systems and data.
Experience with data quality frameworks and schema evolution.
Experience with blue-green or zero-downtime data deployments.
Work Arrangement
Four days per week onsite.
Morning work schedule.
No travel required.
About HTC Global Services
HTC Global Services is a global provider of IT and Business Process Services and Solutions. Founded in 1990, HTC is headquartered in Troy, Michigan with delivery centers across multiple locations in North America, Europe, India, and Malaysia. HTC is an Inc. 500 Hall of Fame company and has been recognized by numerous industry and trade publications as a top provider of services. HTC has a strong client base of Global 2000 customers. HTC has a strong focus on healthcare, retail, financial services, and automotive verticals. HTC has a strong commitment to corporate social responsibility and has been recognized for its contributions to the community.
