AI/ML Engineer II

This is a fully remote position, open to applicants in India.

📋 Description

• Convert business objectives into quantifiable ML goals, KPIs, and acceptance criteria in collaboration with PMs and data scientists.

• Clarify vague product requirements into distinct ML metrics and success parameters.

• Manage the entire process from prototyping, which includes deep learning and GenAI, to deployment and monitoring.

• Create and sustain observability dashboards and alerts linked to ML metrics and feature drift.

• Operate and secure models in real-time environments.

• Promote cross-functional collaboration and governance practices.

• Experiment with new ML tools and frameworks and lead their integration into production when appropriate.

• Design a data strategy that emphasizes reproducibility, traceability, and quality across the ML ecosystem.

• Drive the adoption of emerging ML trends through strategic proof of concepts (POCs) and production implementations.

• Align product, infrastructure, legal, and UX stakeholders on responsible ML practices.

• Support data cleaning, feature engineering, basic ML model testing, scripting, deployment, data pipelines, documentation, and unit testing as per role requirements.

• Oversee ML solution design, production deployments, inference optimization, MLOps practices, and AI projects at advanced levels.

• Architect comprehensive AI services and platforms, encompassing IT ticket routing, network anomaly detection, service desk NLP, and asset-tracking computer vision.

• Develop enterprise AI roadmaps, governance protocols, compliance measures, model standards, and strategic AI initiatives at senior levels.

• Integrate scalable ML models into IT service management systems and supervise cross-domain projects.

• Analyze and refine datasets, identify root causes for data/model issues, select and optimize algorithms, and design scalable solutions.

• Collaborate across functions, elucidate model behavior, mentor junior team members, present insights, and engage with partners or clients.

• Manage projects throughout design, development, testing, rollout, timelines, quality, and multi-team delivery.

• Establish AI strategy, ethics, governance, technical vision, and organizational standards.

⛳️ Requirements

• Level 1: 1–2 years of experience in data science/ML roles; proficient with frameworks like scikit-learn or PyTorch.

• Level 2: 1–2 years of experience in data science/ML roles; adept with frameworks like scikit-learn or PyTorch.

• Level 3: 4–6 years of experience in ML/AI implementation and deployment.

• Level 4: 7–9 years of experience; domain expertise in fields such as IT operations or security AI.

• Level 5: Over 10 years in software engineering with leadership experience in AI/ML.

• Preferred certifications include Google Cloud Professional Machine Learning Engineer, AWS Certified Machine Learning – Specialty, Microsoft Certified: Azure AI Engineer Associate, TensorFlow Developer Certificate, Databricks Certified Machine Learning Professional, and Kubernetes or Docker certification for MLOps roles.

• Proficiency in machine learning techniques including regression, classification, and clustering.

• Familiarity with deep learning architectures such as CNNs, RNNs, Transformers, and LLMs.

• Knowledge of NLP techniques, including tokenization, BERT, and prompt engineering.

• Understanding of Big Data fundamentals, including Spark and Hadoop.

• Awareness of model interpretability, AI ethics, and bias detection.

• Experience with cloud-native AI services such as AWS SageMaker, GCP Vertex AI, and Azure ML.

• Knowledge of data governance, security, and ethical AI practices.

• Proficient in Python; knowledge of Java/C++ is optional; SQL is required.

• Familiarity with frameworks such as TensorFlow, PyTorch, scikit-learn, and Hugging Face.

• Experience with tools including Git, Docker, Kubernetes, Airflow, MLflow, Jupyter, and Postman.

• Skills in data pipeline technologies, including SQL, Pandas, and data APIs.

• Experience with deployment technologies such as Flask/FastAPI, CI/CD, REST APIs, and cloud functions.

• Strong analytical and debugging capabilities.

• Ability to translate business challenges into AI-driven solutions.

• Effective communication skills with both technical and non-technical stakeholders.

• Experience working in Agile or DevOps-based environments.

• Ability to collaborate effectively across globally distributed teams.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible work hours and remote work options.

• Opportunities for professional development and continuous learning.

• Collaborative and innovative work environment.