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Artificial Intelligence Specialist
Job Location:
Job Location:
Dearborn, MI - USA
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
8 September 2026 (13 hours ago)
Posted:
Application Deadline:
6 December 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
V2Soft is a global leader in IT services and business solutions delivering innovative and cost-effective technology solutions worldwide since 1998. We have We have headquartered in Bloomfield Hills MI and have 16 offices spread across six countries. We partner with Fortune 500 companies to address complex business challenges. Our services span AI IT staffing cloud computing engineering mobility testing and more. Certified with CMMI Level 3 and ISO standards V2Soft is committed to quality and security. Beyond our work we actively support local communities and non-profits reflecting our core values. Join us to be part of a dynamic and impactful global company!
Please visit us at to know more.
Only W2 No C2C - 4 Days onsite at Dearborn MI
Skills Required:
Technical Communication Communications Google Cloud Platform TensorFlow Data Governance Machine Learning Python Artificial Intelligence & Expert Systems 1. Technical Communication 25 years translating complex technical concepts such as ML model behavior data pipeline architecture or platform design decisions into clear documentation proposals and presentations for both technical and non-technical audiences including engineering leads and product stakeholders. 2. Communications 25 years of demonstrated ability to communicate effectively across cross-functional teams including facilitating technical discussions contributing to design reviews and keeping stakeholders aligned on project status risks and decisions. 3. Google Cloud Platform 25 years of hands-on experience with GCP services relevant to AI/ML and data workloads including Vertex AI BigQuery GCS Dataflow or Cloud Composer with the ability to deploy and manage workloads in a production cloud environment. 4. TensorFlow 25 years building training and evaluating machine learning models using TensorFlow or TensorFlow Extended (TFX) including experience with model versioning pipeline integration and deploying models to production serving infrastructure. 5. Data Governance 24 years applying data governance principles including data lineage access controls metadata management and compliance standards to ensure telemetry and ML datasets meet quality security and regulatory requirements. 6. Machine Learning 35 years of applied ML experience including feature engineering model selection training validation and deployment. Candidate should be comfortable working with both structured and unstructured data in the context of real-world engineering or automotive telemetry use cases.7. Python 35 years writing production-quality Python for data engineering ML pipeline development or platform tooling. Proficiency with relevant libraries such as Pandas NumPy scikit-learn and TensorFlow is expected along with familiarity with code quality practices such as testing and version control. 8. Artificial Intelligence & Expert Systems 35 years of experience designing or working with AI systems including the application of large language models expert systems or intelligent automation within developer or data workflows. Candidate should understand model lifecycle management prompt engineering and responsible AI practices.
Experience Required:
5 or more years of professional experience in machine learning engineering AI systems development or applied AI research Hands-on experience fine-tuning LLMs in a cloud environment with specific preference for Google Cloud Vertex AI or equivalent managed ML platforms Demonstrated experience building agentic AI systems using frameworks such as LangChain LangGraph Google Agent Builder or equivalent orchestration tooling Proficiency in Python and ML development tooling including Hugging Face PyTorch or TensorFlow and MLflow or Vertex AI Experiments Experience designing and evaluating LLM outputs for production systems including prompt engineering retrieval-augmented generation (RAG) architectures and model evaluation metrics Strong understanding of MLOps practices including model versioning deployment pipelines monitoring and retraining workflows on GCP Experience working in regulated or IP-sensitive environments where model artifact ownership and data governance are active concerns Strong written and verbal communication skills; ability to translate technical AI concepts for non-technical executive stakeholders
Education Required:
Bachelors Degree
Additional Information :
***HYBRID / 4 days per week in the office)
V2Soft is an Equal Opportunity Employer ( EOE). We welcome applicants from all backgrounds including individuals with disabilities and veterans.
- to view all of our open opportunities and to learn more about our benefits.
Please visit us at to know more.
Only W2 No C2C - 4 Days onsite at Dearborn MI
Skills Required:
Technical Communication Communications Google Cloud Platform TensorFlow Data Governance Machine Learning Python Artificial Intelligence & Expert Systems 1. Technical Communication 25 years translating complex technical concepts such as ML model behavior data pipeline architecture or platform design decisions into clear documentation proposals and presentations for both technical and non-technical audiences including engineering leads and product stakeholders. 2. Communications 25 years of demonstrated ability to communicate effectively across cross-functional teams including facilitating technical discussions contributing to design reviews and keeping stakeholders aligned on project status risks and decisions. 3. Google Cloud Platform 25 years of hands-on experience with GCP services relevant to AI/ML and data workloads including Vertex AI BigQuery GCS Dataflow or Cloud Composer with the ability to deploy and manage workloads in a production cloud environment. 4. TensorFlow 25 years building training and evaluating machine learning models using TensorFlow or TensorFlow Extended (TFX) including experience with model versioning pipeline integration and deploying models to production serving infrastructure. 5. Data Governance 24 years applying data governance principles including data lineage access controls metadata management and compliance standards to ensure telemetry and ML datasets meet quality security and regulatory requirements. 6. Machine Learning 35 years of applied ML experience including feature engineering model selection training validation and deployment. Candidate should be comfortable working with both structured and unstructured data in the context of real-world engineering or automotive telemetry use cases.7. Python 35 years writing production-quality Python for data engineering ML pipeline development or platform tooling. Proficiency with relevant libraries such as Pandas NumPy scikit-learn and TensorFlow is expected along with familiarity with code quality practices such as testing and version control. 8. Artificial Intelligence & Expert Systems 35 years of experience designing or working with AI systems including the application of large language models expert systems or intelligent automation within developer or data workflows. Candidate should understand model lifecycle management prompt engineering and responsible AI practices.
Experience Required:
5 or more years of professional experience in machine learning engineering AI systems development or applied AI research Hands-on experience fine-tuning LLMs in a cloud environment with specific preference for Google Cloud Vertex AI or equivalent managed ML platforms Demonstrated experience building agentic AI systems using frameworks such as LangChain LangGraph Google Agent Builder or equivalent orchestration tooling Proficiency in Python and ML development tooling including Hugging Face PyTorch or TensorFlow and MLflow or Vertex AI Experiments Experience designing and evaluating LLM outputs for production systems including prompt engineering retrieval-augmented generation (RAG) architectures and model evaluation metrics Strong understanding of MLOps practices including model versioning deployment pipelines monitoring and retraining workflows on GCP Experience working in regulated or IP-sensitive environments where model artifact ownership and data governance are active concerns Strong written and verbal communication skills; ability to translate technical AI concepts for non-technical executive stakeholders
Education Required:
Bachelors Degree
Additional Information :
***HYBRID / 4 days per week in the office)
V2Soft is an Equal Opportunity Employer ( EOE). We welcome applicants from all backgrounds including individuals with disabilities and veterans.
- to view all of our open opportunities and to learn more about our benefits.
Required Experience:
IC
