Machine Learning Engineer

Apptoza Inc.

Canada · Contract · Mid-Senior

Hi ,

Hope you are doing Great,

I believe this opportunity could be worth exploring. If you’re open to discussing this further, I would love to discuss with you! Please feel free to reply to this email or let me know a good time for a call.

(Note : If you are not Interested, please Share this to your Friends/Colleagues )

GCP Data Engineer / MLOps Engineer

Mississauga, ON - 3 Days Onsite in a Week

Contract : 6Months

Skill required:

1. Cloud Platforms & Services (Google Cloud):

o Google Cloud Platform (GCP) services: AI Platform (Vertex AI), Cloud Storage, BigQuery, Cloud Functions, Cloud Pub/Sub, Cloud Build, Airflow, and Cloud Run.

o Element Platform visibility

2. ML & Data Engineering:

o Understanding of ML concepts and LLM’s (training, validation, hyperparameter tuning, evaluation).

o Experience with TensorFlow, Keras, PyTorch, and scikit-learn.

o Data preprocessing, ETL, and data pipelines using pyspark/Scala using serverless dataproc

3. CI/CD for ML (MLOps):

o Knowledge of CI/CD tools Looper pro/Jenkins.

o Model versioning, continuous training, and deployment using Vertex AI pipelines.

4. Automation & Scripting:

o Strong programming skills in Python, Bash, and SQL

o Automation of workflows and ML pipelines.

5. DevOps & Containerization:

o Kubernetes (GKE) and Docker for containerization and orchestration.

o Good to have Helm charts and YAML for Kubernetes deployments.

6. Monitoring & Observability:

o Cloud Monitoring, Cloud Logging, Prometheus, and Grafana for monitoring and alerting.

o Model performance monitoring with Vertex AI Model Monitoring.

7. Security & Compliance:

o Understanding of VPC, firewall rules, and service accounts.

o Managing secrets using Secret Manager.

8. Data Science

o Must understand general data science methods and the development life cycle

Regards

Rakesh Ummadi

Apptoza Inc

647-557-6949

[email protected]

Website: www.apptoza.com

Key Skills

Ranked by relevance

cloud ai kubernetes cicd google cloud platform containerization serverless prometheus tensorflow firewall grafana storage pytorch python docker devops keras mlops bash gcp etl

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