AIML GCP Engineer

Job Summary

We are looking for a Machine Learning Engineer (AI/ML) with 35 years of experience to develop and deploy scalable AI models. The ideal candidate has handson experience with machine learning algorithms deep learning frameworks and cloudbased ML solutions. You will work on realworld AI applications optimize ML models and collaborate with data scientists software engineers and product teams to deliver AIpowered solutions.

Key Responsibilities

• Develop train and deploy ML models for applications in NLP computer vision recommendation systems or predictive analytics.
• Design and implement ML pipelines for model training validation and deployment.
• Preprocess and analyze large datasets to extract meaningful insights and improve model performance.
• Optimize and finetune ML models using techniques like feature engineering hyperparameter tuning and distributed training.
• Deploy ML models in production using MLOps best practices with cloud platforms (GCP AWS or Azure).
• Collaborate with crossfunctional teams to integrate AI models into production systems.
• Monitor and maintain deployed models ensuring their performance and retraining when necessary.
• Stay uptodate with industry trends emerging AI/ML technologies and best practices.

Qualifications :

• Bachelors or Masters degree in Computer Science Data Science AI or a related field.
• 35 years of experience in machine learning AI or data science roles.
• Strong programming skills in Python (TensorFlow PyTorch Scikitlearn Pandas NumPy).
• Experience in building and deploying ML models on cloud platforms (Google Cloud Platform AWS or Azure).
• Handson experience with ML algorithms (classification regression clustering reinforcement learning).
• Familiarity with deep learning architectures (CNNs RNNs Transformers GANs).
• Understanding of MLOps practices (CI/CD pipelines model monitoring and retraining).
• Experience working with largescale datasets using SQL BigQuery or Spark.
• Knowledge of containerization and orchestration using Docker and Kubernetes.

Additional Information :

Discover some of the global benefits that empower our people to become the best version of themselves:

• Finance: Competitive salary package share plan company performance bonuses valuebased recognition awards referral bonus;   
• Career Development: Career coaching global career opportunities nonlinear career paths internal development programmes for management and technical leadership;
• Learning Opportunities: Complex projects rotations internal tech communities training certifications coaching online learning platforms subscriptions passiton sessions workshops conferences;
• WorkLife Balance: Hybrid work and flexible working hours employee assistance programme;
• Health: Global internal wellbeing programme access to wellbeing apps;
• Community: Global internal tech communities hobby clubs and interest groups inclusion and diversity programmes events and celebrations.

Our diversity makes us stronger it drives meaningful change and enables us to build innovative technology solutions. We are committed to creating an inclusive community where all of us regardless of background identity or personal characteristics feels valued respected and free from discrimination. As an equal opportunity employer we welcome applications from all individuals and base hiring decisions on merit skills qualifications and potential.

Remote Work :

No

Employment Type :

Fulltime