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Accenture

Advises businesses and runs their technology

Custom Software Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • A minimum of 7.5 years of experience in machine learning is required.
  • A proven record of architecting and shipping production machine learning and large language model systems is required.
  • Strong written and verbal communication experience leading Agile delivery and cross-functional collaboration is required.
  • Proven experience in cloud, DevOps, or AI modernization initiatives is required.
  • A strong understanding of large language models, automation, and engineering toolchains is required.
  • The ability to translate AI innovation into business and productivity impact is required.
  • The candidate must have at least 15 years of full-time education.
  • Expected technical knowledge includes model generalization versus overfitting and underfitting, bias/variance trade-offs, regularization, and early stopping.
  • Expected technical knowledge includes deep learning fundamentals such as convolutional neural networks, recurrent neural networks, long short-term memory networks, gated recurrent units, transformers, encoder/decoder architectures, and attention.
  • Expected practical knowledge of large language model internals includes tokenization, context windows, inference strategies such as batching, caching and quantization, fine-tuning/parameter-efficient fine-tuning, and retrieval-augmented generation.
  • Expected inference and serving knowledge includes vectorization, mixed precision, and applicable compilation or acceleration paths.
  • Professional and technical skills include PyTorch; the Hugging Face ecosystem, including Transformers, Datasets, and Sentence Transformers; and applicable BERT and Llama model families.
  • Professional and technical skills include LangChain and familiarity with LangGraph and LangMem for agentic workflows, subject to approval.
  • Professional and technical skills include spaCy, scikit-learn, LightGBM, Flair where relevant, Optuna for hyperparameter optimization, and SHAP for model explainability.
  • Professional and technical skills include Elastic or OpenSearch, vector stores such as FAISS, Pinecone, or pgvector, and docarray for embedding flows.
  • Professional and technical skills include Playwright or Selenium, Trafilatura, pypdf, pdfplumber, pdfkit, and tokenization tools such as tiktoken.
  • Professional and technical skills include Streamlit for local-only stakeholder demonstrations.

Responsibilities

  • Define end-to-end architecture for large language model and agent systems, including tool use, orchestration, and guardrails, as well as classical machine learning components.
  • Design suggestion engines and policy/rule layers that combine deterministic constraints with generative outputs.
  • Architect search and retrieval using BM25 and embeddings, and retrieval-augmented generation pipelines; drive relevance tuning and evaluation.
  • Oversee robust web scraping and extraction using tools such as Playwright, Selenium, and Trafilatura, and structured normalization using JSON/Parquet and schema validation.
  • Direct image processing and optical character recognition workflows for document understanding, using tools such as OpenCV, pytesseract, and ocrmypdf.
  • Establish evaluation strategies involving offline/online experiments and quality, latency, and cost key performance indicators; integrate DeepEval for unit-style large language model testing.
  • Guide data governance, privacy and personally identifiable information handling, and secure model and agent operations with MLOps partners.
  • Mentor the team, run design reviews, and produce design documents, RFCs, and POVs for stakeholders.
  • Lead the design and delivery of AI solutions across agentic AI, generative AI including large language models, and classical machine learning and computer vision.
  • Own the technical direction for suggestion and rules frameworks, search and retrieval, document and web data extraction, and image and optical character recognition pipelines for the Value Stream.
  • Provide architectural leadership and ensure production-grade quality, safety, and reliability.
  • Work with the team to deliver reliable and innovative tax technology solutions.

About the Company

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Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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