Sr MachineLearning Engineer

Senior Machine Learning Engineer

Experience Level: 5-7 years

Note : Looking for Immediate Joiners and Serving Np lessthan 15 days

Mandatory Skills : Gemini or Microsoft copilot , Machine Learning , GCP, Vertex AI

• AndorTech is seeking a highly skilled and experienced Senior Machine Learning
• Engineer with a deep specialization in Google Cloud Platform (GCP) and its
• advanced AI services. In this critical role, you will be instrumental in supporting and
• optimizing our use of the Google AI ecosystem, particularly Gemini Enterprise, and
• ensuring our AI solutions are robust, scalable, and performant. You will work closely
• with internal teams and clients, providing expert guidance, troubleshooting complex
• issues, and driving the adoption of best practices across our AI initiatives.
• Key Responsibilities:
• ● GCP AI Ecosystem Expertise: Serve as a subject matter expert for Google
• Cloud Platforms AI services, with a particular focus on Gemini Enterprise, AI
• Studio, and NotebookLM.
• ● Solution Architecture & Optimization: Design, implement, and optimize
• scalable and cost-effective ML solutions leveraging GCP managed services
• such as Vertex AI, Cloud Run, Cloud Functions, and various database services
• (e.g., Cloud SQL, Firestore, BigQuery).
• ● Gemini Enterprise & Agent Development: Provide advanced technical
• support and guidance for Gemini Enterprise implementations, including
• prompt engineering, model fine-tuning, and the development and
• deployment of AI agents using relevant Agent Development Kits.
• ● Troubleshooting & Problem Solving: Diagnose and resolve complex technical
• issues related to GCP AI services, ML model deployments, data pipelines, and
• infrastructure.
• ● Customer Query Handling: Act as a primary point of contact for internal
• teams and clients, addressing technical queries, providing prompt guidance,
• and offering expert advice on leveraging GCP AI capabilities effectively.
• ● Operational Support: Manage and respond to incoming support requests via
• JIRA and designated MS Teams channels (Gemini AI Support), ensuring
• timely resolution and adherence to service level agreements (SLAs).● Best Practices & Governance: Advocate for and implement best practices in
• MLOps, security, cost optimization, and compliance within the GCP
• environment.
• ● Documentation & Knowledge Sharing: Create and maintain comprehensive
• technical documentation, runbooks, and knowledge base articles to
• empower internal teams and clients.
• ● Collaboration & Mentorship: Collaborate with data scientists, software
• engineers, and product managers to integrate AI solutions, and mentor junior
• engineers on GCP AI best practices.
• ● Stay Current: Continuously research and evaluate new GCP AI services,
• features, and industry trends to recommend innovative solutions.
• Required Skills & Experience:
• ● Bachelors or Masters degree in Computer Science, Machine Learning,
• Artificial Intelligence, or a related quantitative field.
• ● 5+ years of professional experience as a Machine Learning Engineer,
• MLOps Engineer, or a similar role with a strong focus on cloud
• platforms.
• ● Deep expertise in Google Cloud Platform (GCP) services, including:
• ● Vertex AI (especially for model training, deployment, and monitoring)
• ● Gemini Enterprise (hands-on experience with its capabilities and
• integration)
• ● Cloud Run and Cloud Functions for serverless ML inference and
• event-driven architectures.
• ● GCP Database services (e.g., Cloud SQL, Firestore, BigQuery) for data
• storage and retrieval.
• ● Networking and Security concepts within GCP.
• ● Proven experience with large language models (LLMs) and generative
• AI, specifically with Googles Gemini family of models.
• ● Hands-on experience with Agent Development Kits (ADKs) or
• frameworks for building conversational AI agents.
• ● Strong programming skills in Python, including relevant ML libraries
• (e.g., TensorFlow, PyTorch, scikit-learn).● Experience with MLOps practices and tools for CI/CD, version control
• (Git), and automated testing of ML pipelines.
• ● Excellent problem-solving, analytical, and debugging skills.
• ● Strong communication and interpersonal skills, with the ability to
• explain complex technical concepts to both technical and
• non-technical audiences.
• ● Ability to work independently and as part of a team in a fast-paced,
• dynamic environment.
• Preferred Qualifications:
• ● GCP Professional Machine Learning Engineer or Cloud Architect
• certification.
• ● Experience with other Google AI services like AI Studio, NotebookLM.
• ● Familiarity with containerization technologies (Docker, Kubernetes).
• ● Experience working in a support-oriented role, handling customer
• queries and adhering to SLAs.
• ● Understanding of data governance, privacy, and security best
• practices in an AI context.