Machine Learning Engineer #1065247

Fasttek; Dearborn (MI); On-site; USD 110,000 - 160,000; Full time

Benefits offered by this job

Medical & Dental

Vision

PTO

Long-Term Disability

Life Insurance

401(k) with immediate vesting

Job summary

FastTek Global in Dearborn, MI is seeking a Machine Learning Engineer to design, build, deploy, and scale self-running ML solutions across vision and localization domains.

You will automate ML lifecycles with CI/CD/CT and MLOps, collaborating with stakeholders to solve business problems using scalable pipelines and cloud-native tools.

Qualifications

• Experience building ML models and pipelines in production environments.
• Strong software engineering practices with CI/CD and testing.
• Hands-on with GCP-native data/ML tools like Vertex AI and BigQuery.

Responsibilities

• Collaborate with stakeholders to define ML requirements.
• Design and develop ML models and software algorithms for complex problems.
• Build, maintain, and optimize scalable ML pipelines and infrastructure.
• Deploy models into production and run simulations for validation.
• Automate model deployment, training, and re-training using MLOps.

Skills

GCP/BigQuery

Python/Java

Cloud Infrastructure

AI/Expert Systems

Education

Bachelor's Degree

Job description

Dearborn, Michigan Machine Learning Engineer #1065247

Position Description:

Employees in this job function are responsible for designing, building, deploying and scaling complex self-running ML solutions in areas like computer vision, perception, localization etc. They also automate and optimize the end-to-end ML model lifecycle using their expertise in experimental methodologies, statistics, and coding for tool building and analysis.

Key Responsibilities:

• Collaborate with business and technology stakeholders to understand current and future ML requirements
• Design and develop innovative ML models and software algorithms to solve complex business problems in both structured and unstructured environments
• Design, build, maintain and optimize scalable ML pipelines, architecture and infrastructure
• Use machine language and statistical modeling techniques such as decision trees, logistic regression, Bayesian analysis and others to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy
• Adapt machine learning to areas such as virtual reality, augmented reality, object detection, tracking, classification, terrain mapping, and others.
• Train and re-train ML models and systems as required
• Deploy ML models and algorithms into production and run simulations for algorithm development and test various scenarios
• Automate model deployment, training and re‑training, leveraging principles of agile methodology, CI/CD/CT (Continuous Integration/ Continuous Deployment/ Continuous Training) and MLOps
• Enable model management for model versioning and traceability to ensure modularity and symmetry across environments and models for ML systems

Skills Required:

• GCP, Big Query, Python, Java, Cloud Infrastructure, Artificial Intelligence & Expert Systems

Graph Layer

• Design, develop, test, and deploy the ISDP knowledge graph from the domain event store to Production using cloud-native data pipelines.
• Model and evolve the graph's entities and relationships as new data sources are onboarded. MCP serving layer
• Design, build, and operate the MCP server that exposes the ISDP graph layer and event store as tools to consumers — including GQL graph query, event-store query, and schema/DDL discovery.
• Define tool contracts, context, and guardrails so agents produce grounded, accurate, non-hallucinated responses over the graph.
• Ensure low-latency, secure, and cost-efficient serving for interactive and batch agent workloads. Reliability, monitoring & observability
• Own monitoring and observability of the graph layer and the MCP server — data freshness, pipeline health, query latency/cost, tool-call success rates, and answer quality.
• Instrument SLOs, dashboards, alerting, and tracing; drive incident response and continuous reliability improvements. Collaboration & data onboarding
• Partner with Data Engineers and Application Data Source Owners across Product Development, Manufacturing, Quality, and Supply Chain to ingest and validate their data into ISDP.
• Establish data contracts, schema validation, and quality checks; support source owners through onboarding, mapping to the ISDP logical model, and troubleshooting.
• Contribute to data governance, cataloging, and lineage for the graph and its sources.

Experience Required:

• Engineer 2 Exp.: Practitioner: 1 coding language or framework. 7+ years in IT; 3+ years in development 2+ Years in AI and Graph Engineering
• Strong software engineering in Java, Python, with production-grade testing, CI/CD, and code quality practices.
• Hands‑on experience deploying data/AI systems to Production on a GCP-native stack: 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 — property graphs and GQL / graph query patterns (BigQuery property graphs, or equivalent such as Neo4j/Spanner Graph).
• Hands‑on experience with Vertex AI (Agents, model serving, embeddings) and evaluation of agent answer quality.
• Experience building LLM/agent systems: tool‑use, RAG/grounding, and integrating models via APIs (e.g., Vertex AI or enterprise LLM gateways). Familiarity with MCP or comparable agent tool protocols.
• Observability expertise: Cloud Monitoring/Logging, OpenTelemetry, SLOs, dashboards, and alerting for data pipelines and services.
• Infrastructure as Code (Terraform) and secure‑by‑default engineering (IAM, least privilege, secrets management).
• Ability to work directly with data producers to model and validate real‑world industrial/enterprise data.

Experience Preferred:

• Familiarity with Dataplex / Data Catalog for governance, lineage, and business glossaries.
• Streaming/CDC and event-driven architectures; append‑only/event-sourced data modeling.
• Design and build user-facing applications and dashboards that surface Knowledge Graph data to end users.
• Domain exposure to PLM / product development, manufacturing execution, quality, or supply‑chain systems and their data.
• Data quality frameworks, schema evolution, and blue‑green/zero-downtime data deployments.

Education Required:

• Bachelor's Degree

Additional Info:

At FastTek Global, Our Purpose is Our People and Our Planet. We come to work each day and are reminded we are helping people find their success stories. Also, Doing the right thing is our mantra. We act responsibly, give back to the communities we serve and have a little fun along the way.

We have been doing this with pride, dedication and plain, old-fashionedhard work for 24 years!

FastTek Global is financially strong, privately held company that is 100% consultant and client focused.

We've differentiated ourselves by being fast, flexible, creative and honest. Throw out everything you've heard, seen, or felt about every other IT Consulting company. We do unique things and we do them for Fortune 10, Fortune 500, and technology start-up companies.

Our benefits are second to none and thanks to our flexible benefit options you can choose the benefits you need or want, options include:

• Medical and Dental (FastTek pays majority of the medical program)
• Vision
• Personal Time Off (PTO) Program
• Long Term Disability (100% paid)
• Life Insurance (100% paid)
• 401(k) with immediate vesting and 3% (of salary) dollar-for-dollar match

Plus, we have a lucrative employee referral program and an employee recognition culture.

FastTek Global was named one of the Top Work Places in Michigan by the Detroit Free Press in 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, and 2023!

AI & Hiring Disclosure

We use AI tools to support parts of our hiring process, such as reviewing applications and identifying potential matches. These tools are designed to promote efficiency, consistency, and fairness, and they are always used under human oversight.

All personal data collected is used solely for recruitment purposes, and you have the right to know, access, or request deletion of your data at any time, subject to legal limits.

If AI will be used in a video interview, you'll be informed in advance and asked for your consent, with the option to opt out.

Our tools are regularly reviewed to detect potential bias and to ensure compliance with all applicable laws and our commitment to inclusive hiring.

To learn more or exercise your rights, please contact us at [e-mail].