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Job Title: ML Ops Engineer / Google Cloud Platform Data Engineer
Location: Hybrid – 4 Days Onsite
Duration: Long Term Contract
Job Description
We are seeking an experienced ML Ops Engineer / Cloud Data Engineer with strong expertise in building scalable machine learning platforms and cloud-native data pipelines on Google Cloud Platform (Google Cloud Platform). The ideal candidate will have hands-on experience supporting production ML environments, real-time streaming architectures, CI/CD automation, and large-scale data engineering initiatives.
This role will support enterprise AI/ML and connected vehicle initiatives by developing and optimizing robust ML pipelines, monitoring solutions, and cloud infrastructure in an Agile environment.
Required Skills
MLOps, Google Cloud Platform, Google Cloud Platform, BigQuery, Pub/Sub, Kubernetes, Python, Spark, Kafka, Airflow, Terraform, Docker, GitHub, Tekton, CI/CD, Machine Learning, AI, REST API, SQL, Microservices, TensorFlow, Data Engineering, Cloud Architecture
Job Title: ML Ops Engineer / Google Cloud Platform Data Engineer
Location: Hybrid – 4 Days Onsite
Duration: Long Term Contract
Job Description
We are seeking an experienced ML Ops Engineer / Cloud Data Engineer with strong expertise in building scalable machine learning platforms and cloud-native data pipelines on Google Cloud Platform (Google Cloud Platform). The ideal candidate will have hands-on experience supporting production ML environments, real-time streaming architectures, CI/CD automation, and large-scale data engineering initiatives.
This role will support enterprise AI/ML and connected vehicle initiatives by developing and optimizing robust ML pipelines, monitoring solutions, and cloud infrastructure in an Agile environment.
Required Skills
- Strong hands-on experience in MLOps and Machine Learning Platforms
- Expertise with Google Cloud Platform (Google Cloud Platform) including:
- BigQuery
- Pub/Sub
- Kubernetes
- Cloud Storage
- Experience building large-scale batch and streaming pipelines using:
- Apache Kafka
- Spark / Spark SQL
- Airflow
- Microservices architecture
- Strong programming skills in:
- Python
- SQL
- Java/Spark preferred
- Experience with:
- Terraform
- Docker
- GitHub
- Tekton
- CI/CD pipelines
- REST API development/integration experience
- Strong understanding of Data Governance and Cloud Architecture
- Experience working in Agile/TDD environments
- Excellent communication and stakeholder management skills
- TensorFlow
- Telematics / Connected Vehicle Data
- Data Modeling
- Cloud Infrastructure Architecture
- ML Model Monitoring
- Open-source contributions
- Google Cloud Platform Certifications
- Bachelor’s Degree required
- 6 years of relevant experience with Bachelor’s Degree OR
- 4 years with Master’s Degree
- Strong experience supporting production ML/AI pipelines
- Build scalable ML and data pipelines on Google Cloud Platform
- Develop real-time and batch data processing solutions
- Support continuous learning and model monitoring frameworks
- Optimize ML platforms for scalability, performance, security, and cost
- Maintain CI/CD and Infrastructure-as-Code environments
- Collaborate with cross-functional teams and business stakeholders
- Monitor and troubleshoot production data pipelines
- Support AI/Agentic AI initiatives
MLOps, Google Cloud Platform, Google Cloud Platform, BigQuery, Pub/Sub, Kubernetes, Python, Spark, Kafka, Airflow, Terraform, Docker, GitHub, Tekton, CI/CD, Machine Learning, AI, REST API, SQL, Microservices, TensorFlow, Data Engineering, Cloud Architecture