Lead Machine Learning Engineer/ AI Systems Architect

About UsAccenture Industry X, part of Accenture, helps businesses thrive in the digital era by combining data and digital capabilities. Join us to experience how we deliver 360 value and collaborate with exceptional people, cutting-edge technology, and leading companies across various industries, making a significant impact worldwide.We are seeking a Lead Machine Learning Engineer / AI Systems Architect to design and scale enterprise-grade Vehicle Connectivity Data, AI and ML systems that unify predictive modeling, neural networks, Generative AI, and Agentic AI into intelligent, cloud-native platforms, to monitor quality of fleet connectivity and operations.What you need to succeed:Engineering & Architecture FoundationsExpert-level proficiency in Python, with additional experience in Java, Go, or TypeScript for integration and tooling.Strong understanding of distributed systems, API design, and microservice architectures.Proven experience architecting scalable, fault-tolerant AI systems in cloud or hybrid environments.Proficiency with CI/CD, testing frameworks, and infrastructure-as-code (Terraform, Pulumi).Hands-on experience with monitoring and observability stacks (Prometheus, Grafana, OpenTelemetry).Demonstrated ability to balance innovation with operational reliability, ensuring resilient deployments.Machine Learning & Neural Network SystemsDeep experience building and deploying machine learning models, spanning classical algorithms (regression, boosting, SVMs) and neural architectures (CNNs, RNNs, Transformers).Expertise in feature engineering, data preprocessing, model lifecycle management, and explainability (XAI).Proven ability to design end-to-end ML pipelines — from data ingestion to serving and continuous evaluation.Skilled in MLOps: experiment tracking, versioning, automated retraining, and monitoring (MLflow, Kubeflow, DVC, SageMaker, Vertex AI, Azure ML).Experience with distributed training, GPU optimization, and real-time inference at scale.Familiarity with reinforcement learning, causal inference, and graph-based reasoning for advanced analytics.Strong understanding of evaluation frameworks for both predictive and generative systems.Cloud Infrastructure & ScalabilityDeep knowledge of cloud-native architectures (AWS, Azure, GCP) and their AI/ML ecosystems.Skilled in containerization (Docker) and orchestration (Kubernetes) for scalable AI services.Proven ability to design secure, cost-optimized, and compliant AI infrastructure.Expertise in distributed inference, GPU/TPU orchestration, and scalable model serving.Experience integrating logging, alerting, and observability into AI pipelines.Familiarity with multi-modal workloads (text, image, audio, code) and their deployment patterns.Data & Knowledge SystemsStrong understanding of data architecture, ETL, and data modeling for AI workloads.Proficiency with embedding models and vectorization for semantic search, personalization, and context retrieval.Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, Chroma) and knowledge graphintegration.Ability to design retrieval-augmented generation (RAG) pipelines combining structured and unstructured data.Skilled in embedding optimization, context compression, and persistent memory architectures for long-running agents.Awareness of data governance, lineage, and privacy-preserving AI principles.Generative AI & Agentic AI IntegrationDeep familiarity with LLMs (e.g., GPT, Claude, Gemini, Llama) and foundation model APIs.Ability to design systems that blend predictive ML and neural models with Generative AI layers (text synthesis, reasoning, summarization, code generation).Experience with fine-tuning, LoRA, and adapter-based model customization.Understanding of agent-based reasoning architectures — systems where AI models plan, act, and collaborate via reasoning loops (e.g., ReAct, planner–executor, multi-agent).Skilled in building agent orchestration layers using LangChain, AutoGen, CrewAI, or LlamaIndex.Experience integrating LLMs with data pipelines, APIs, and enterprise tools to enable adaptive, semi-autonomous workflows.Ability to define evaluation and observability frameworks for GenAI and Agentic systems, including coherence, accuracy, and hallucination control.Your life at AccentureAt Accenture, we prioritize your health and well-being through comprehensive health insurance coverage and inclusive work arrangements. We value your growth and offer diverse learning and development paths, along with performance-based rewards. You'll also have access to resources for mental health and physical wellness, ensuring inclusivity and support. We provide additional financial support, flexible benefits, and care for your loved ones, respecting diverse circumstances.Join us for a fulfilling career and a balanced lifestyle that celebrates diversity and promotes inclusivity.The position is available exclusively for collaboration under an individual working contract (CIM).