CrawlJobs Logo

ML Engineer Senior - GenAI Solutions

nttdata.com Logo

NTT DATA

Location Icon

Location:
Italy , Milano

Category Icon

Job Type Icon

Contract Type:
Not provided

Salary Icon

Salary:

Not provided

Job Description:

As a Senior Machine Learning Engineer at NTT DATA, you will work alongside experienced Data Scientists, Data and ML Engineers on advanced machine learning and Generative AI initiatives.

Job Responsibility:

  • Apply hands-on Generative AI capabilities, preferably on Azure/GCP and on-premise GenAI architectures and MLOps
  • Leverage a strong mathematical background
  • Work on classification, information retrieval, clustering and optimization problems
  • Establish scalable, efficient and automated processes for large-scale data analysis
  • Contribute to model development, model validation and model implementation
  • Identify business opportunities
  • Design and create new data pipelines from scratch, from experiments to production deployment
  • Manage multiple projects
  • Lead ML Engineers
  • Connect with stakeholders

Requirements:

  • At least 5 years of production experience working in Data Science or Software Engineering
  • Deep knowledge of math, probability, statistics and algorithms
  • At least 6/12 months of experience in Generative AI deployment and underlying architecture handling
  • Vector Database knowledge is well appreciated
  • Understanding of data structures, data modeling and software architecture
  • Fluent in a at least two mainstream programming language (Python, Scala, Java, C++)
  • Experience in building an infrastructure for technical users, such as Data Scientist, ML practitioners or data consumers/producers
  • Strong knowledge of Spark, Databricks is a strong plus
  • Experience developing/deploying ML solutions in one of the public cloud platforms and on a Cross-cloud base, Snowflake knowledge is a plus
  • Deep knowledge with machine learning frameworks (such as Keras or PyTorch)
  • Ability to design and implement machine learning pipelines in a production environment
  • Experience with deployment including knowledge of CI/CD, containerization, and related concepts with a focus over MLops/Re-Training/Drift Management
  • Ability to train more junior team members in multiple Machine Learning and Deep Learning concepts
  • Establish and maintain strong relationships with internal team members and external clients

Nice to have:

  • Vector Database knowledge
  • Snowflake knowledge
  • Experience with Databricks

Additional Information:

Job Posted:
May 14, 2026

Employment Type:
Fulltime
Work Type:
On-site work
Job Link Share:

Looking for more opportunities? Search for other job offers that match your skills and interests.

Briefcase Icon

Similar Jobs for ML Engineer Senior - GenAI Solutions

Senior Machine Learning Engineer

We’re seeking a Senior Machine Learning Engineer (P50) to join our new GenAI Mod...
Location
Location
Singapore
Salary
Salary:
Not provided
https://www.atlassian.com Logo
Atlassian
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Extensive experience (generally 5+ years) in ML systems engineering, backend engineering, or infrastructure roles
  • Strong background in one or more of: LLMs, NLP, search/retrieval, embeddings, or applied ML
  • Hands-on experience with at least one GenAI area: RAG pipelines, fine-tuning, hybrid retrieval, or orchestration frameworks
  • Proficiency with modern ML frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex)
  • Familiarity with vector databases (Weaviate, Pinecone, FAISS, etc.) and large-scale serving infra
  • Strong coding skills (Python, backend engineering) and ability to move fast from idea to prototype
  • Comfort working in fast-paced, experimental environments with evolving direction
  • Bachelor’s or Master’s in Computer Science, Machine Learning, or related field—or equivalent experience
Job Responsibility
Job Responsibility
  • Build and apply advanced GenAI models
  • Develop and fine-tune LLMs and embeddings for Atlassian’s unique knowledge and enterprise data
  • Implement retrieval-augmented generation (RAG), hybrid retrieval, and knowledge-grounded modeling approaches
  • Work hands-on with modern frameworks, contributing directly to high-value prototypes and experiments
  • Prototype and experiment quickly
  • Build proof-of-concept systems for GenAI-powered assistants, agentic workflows, and innovative user experiences
  • Run experiments, collect feedback, and iterate fast to validate impact
  • Design and implement evaluation methods for quality, groundedness, and user value
  • Collaborate and contribute
  • Work closely with peers across ML, engineering, and product teams to bring new ideas to life
What we offer
What we offer
  • Health and wellbeing resources
  • Paid volunteer days
Read More
Arrow Right

Senior Software Engineer – AI

NStarX is seeking a highly skilled Senior Software Engineer – AI with a strong f...
Location
Location
India , Hyderabad
Salary
Salary:
Not provided
nstarxinc.com Logo
NStarX
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field (PhD is a plus)
  • 9+ years of experience in AI/ML engineering or related roles
  • 3+ years of experience in Generative AI with team leadership responsibilities
  • Proven track record of production-grade ML and GenAI model development and deployment
  • Programming: Python (preferred)
  • GenAI Frameworks: Hugging Face Transformers, Diffusers, LangChain, TGI
  • Serving & Inference: FastAPI, gRPC, NVIDIA Triton, TorchServe
  • Cloud Platforms: AWS (SageMaker, EKS), GCP (Vertex AI, GKE), Azure (Azure ML, AKS)
  • MLOps & DevOps: Kubeflow, MLflow, GitHub Actions, Jenkins, Helm, Terraform
  • Optimization Techniques: Model quantization, distillation, pipeline and tensor parallelism
Job Responsibility
Job Responsibility
  • Design, develop, and deploy machine learning models and AI algorithms to address complex business challenges
  • Lead and mentor a team of AI/ML engineers, ensuring quality and scalability in solution design and implementation
  • Collaborate closely with cross-functional teams including data scientists, software engineers, product managers, and UX designers
  • Lead the development and deployment of Generative AI applications across text, code, image, and audio modalities using state-of-the-art LLMs
  • Design and implement CI/CD pipelines for the GenAI model lifecycle including training, validation, packaging, and deployment
  • Apply best practices for model performance tuning, cost optimization, and scalable deployment in cloud and hybrid environments
  • Develop prompt engineering, fine-tuning strategies (LoRA, QLoRA, PEFT), and evaluation protocols tailored to business use cases
  • Stay current with emerging trends in AI, ML, and Generative AI and drive adoption across teams
  • Document processes, model architectures, and deployment strategies for traceability and knowledge sharing
  • Work closely with cross-functional teams to gather requirements and deliver high-quality solutions
What we offer
What we offer
  • Competitive salary aligned with market standards
  • Opportunities for professional development and skill enhancement
  • A collaborative and innovative work environment
  • Fulltime
Read More
Arrow Right

ML Tech Lead, GenAI

Provectus helps companies adopt ML/AI to transform the ways they operate, compet...
Location
Location
Salary
Salary:
Not provided
provectus.com Logo
Provectus
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Proven experience with LLMs and NLP frameworks (e.g., Hugging Face, OpenAI, or Anthropic models)
  • Strong expertise in AWS Cloud Services
  • Strong experience in ML/AI, including at least 2 years in a leadership role
  • Hands-on experience with Python, TensorFlow/PyTorch, and model optimization
  • Familiarity with MLOps tools and best practices
  • Excellent problem-solving and decision-making abilities
  • Strong communication skills and the ability to lead cross-functional teams
  • Passion for mentoring and developing engineers
Job Responsibility
Job Responsibility
  • Lead and manage a team of 5-10 engineers, providing mentorship and fostering a collaborative team environment
  • Drive the roadmap for machine learning projects aligned with business goals
  • Coordinate cross-functional efforts with product, data, and engineering teams to ensure seamless delivery
  • Design, develop, and fine-tune LLMs and other machine learning models to solve business problems
  • Evaluate and implement state-of-the-art LLM techniques for NLP tasks such as text generation, summarization, and entity extraction
  • Stay ahead of advancements in LLMs and apply emerging technologies
  • Expertise in multiple main fields of ML: NLP, Computer Vision, RL, deep learning and classical ML
  • Architect and manage scalable ML solutions using AWS services (e.g., SageMaker, Lambda, Bedrock, S3, ECS, ECR, etc.)
  • Optimize models and data pipelines for performance, scalability, and cost-efficiency in AWS
  • Ensure best practices in security, monitoring, and compliance within the cloud infrastructure
Read More
Arrow Right

Senior Machine Learning Systems Engineer

Our organization drives AI innovation across Jira products. We deliver seamless ...
Location
Location
Salary
Salary:
Not provided
https://www.atlassian.com Logo
Atlassian
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Extensive experience building Machine Learning and AI solutions (4+ years)
  • Proven experience developing, deploying, and maintaining end-to-end ML systems, including data engineering, model serving, and monitoring
  • Expert proficiency with GenAI frameworks and tools, including developing and fine-tuning large language models (LLMs) and building retrieval-augmented generation (RAG) systems
  • Expert proficiency in Python and ML frameworks like PyTorch, TensorFlow, or JAX
  • Experience implementing MLOps, CI/CD pipelines, and automation for continuous training, deployment, and monitoring of ML models
Job Responsibility
Job Responsibility
  • Collaborate with software engineers, data scientists, and product managers to solve complex problems
  • Lead projects from technical design through launch
  • Partner with teams to achieve impactful results
  • Deliver robust ML solutions to build AI features reaching millions
  • This includes curating ML datasets, fine-tuning open-source LLMs, or accessing proprietary LLMs
  • Mentor junior members of the team
What we offer
What we offer
  • Health and wellbeing resources
  • Paid volunteer days
Read More
Arrow Right

Gen AI Engineering and Scaled AI Transformation

Location
Location
Canada , Mississauga
Salary
Salary:
145100.00 - 217700.00 USD / Year
https://www.citi.com/ Logo
Citi
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • 10+ years of progressive experience in software engineering, ML, or AI platforms, with 5+ years leading senior engineers and architects
  • 3+ years of hands‑on experience deploying LLM‑based systems in production environments at enterprise scale
  • Demonstrated authority across commercial and open‑source LLM ecosystems (e.g., OpenAI, Anthropic, Google, Llama), including model selection, fine‑tuning, and hosting strategies
  • Proven ability to define enterprise-wide GenAI standards, reference architectures, and reusable accelerators
  • Demonstrated leadership in establishing prompt engineering standards and orchestration patterns
  • Experience optimizing latency, throughput, accuracy, and token cost across large‑scale GenAI workloads
  • Bachelor’s degree/University degree or equivalent experience
  • Master’s degree preferred
Job Responsibility
Job Responsibility
  • Acts as a senior technical authority on Large Language Models, including both commercial and open‑source ecosystems (OpenAI, Gemini, Claude, Llama)
  • Leads model selection and deployment strategy, balancing use‑case fit, data sensitivity, cost efficiency, latency, accuracy, and regulatory constraints
  • Guides decisions on hosted vs. private vs. fine‑tuned models, ensuring optimal trade‑offs between performance, control, and operational risk
  • Establishes enterprise standards for LLM lifecycle management, including upgrades, regression validation, and decommissioning
  • Demonstrates hands‑on leadership in building GenAI applications using LangChain, LangGraph, LlamaIndex, and Hugging Face, translating experimentation into production systems
  • Architects agentic and multi‑step workflows, enabling tool‑use, reasoning chains, state management, and orchestration at enterprise scale
  • Sets reusable reference patterns and accelerators for GenAI adoption across application teams
  • Ensures solutions are built with enterprise-grade reliability, explainability, and extensibility
  • Designs and delivers robust RAG architectures that ground GenAI outputs in trusted, auditable enterprise data
  • Leads implementation of vector databases and embedding strategies (pgvector, Pinecone, Weaviate, FAISS), aligned with data access and security models
  • Fulltime
Read More
Arrow Right

Senior ML Engineer (GenAI, AWS)

Provectus helps companies adopt ML/AI to transform the ways they operate, compet...
Location
Location
Colombia , Medellín; Bogotá; Cali; Barranquilla; Bucaramanga
Salary
Salary:
Not provided
provectus.com Logo
Provectus
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • ML Fundamentals: supervised, unsupervised, and reinforcement learning
  • Model Development: feature engineering, model training, evaluation, hyperparameter tuning, and validation
  • ML Frameworks: classical ML libraries, TensorFlow, PyTorch, or similar frameworks
  • Deep Learning: CNNs, RNNs, Transformers
  • LLM Applications: Experience building production LLM-based applications
  • Prompt Engineering: Ability to design effective prompts and chain-of-thought strategies
  • RAG Systems: Experience building retrieval-augmented generation architectures
  • Vector Databases: Familiarity with embedding models and vector search
  • LLM Evaluation: Experience with evaluation metrics and techniques for LLM outputs
  • Python: Advanced proficiency in Python for ML applications
Job Responsibility
Job Responsibility
  • Design and implement end-to-end ML solutions from experimentation to production
  • Build scalable ML pipelines and infrastructure
  • Optimize model performance, efficiency, and reliability
  • Write clean, maintainable, production-quality code
  • Conduct rigorous experimentation and model evaluation
  • Troubleshoot and resolve complex technical challenges
  • Mentor junior and mid-level ML engineers
  • Conduct code reviews and provide constructive feedback
  • Share knowledge through documentation, presentations, and workshops
  • Collaborate with cross-functional teams (DevOps, Data Engineering, SAs)
What we offer
What we offer
  • Long-term B2B collaboration
  • Fully remote setup
  • A budget for your medical insurance
  • Paid sick leave, vacation, public holidays
  • Continuous learning support, including unlimited AWS certification sponsorship
  • Fulltime
Read More
Arrow Right

Senior ML Engineer (GenAI)

Provectus helps companies adopt ML/AI to transform the ways they operate, compet...
Location
Location
Colombia , Medellín; Bogotá; Cali; Barranquilla; Bucaramanga
Salary
Salary:
Not provided
provectus.com Logo
Provectus
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • ML Fundamentals: supervised, unsupervised, and reinforcement learning
  • Model Development: feature engineering, model training, evaluation, hyperparameter tuning, and validation
  • ML Frameworks: classical ML libraries, TensorFlow, PyTorch, or similar frameworks
  • Deep Learning: CNNs, RNNs, Transformers
  • LLM Applications: Experience building production LLM-based applications
  • Prompt Engineering: Ability to design effective prompts and chain-of-thought strategies
  • RAG Systems: Experience building retrieval-augmented generation architectures
  • Vector Databases: Familiarity with embedding models and vector search
  • LLM Evaluation: Experience with evaluation metrics and techniques for LLM outputs
  • Python: Advanced proficiency in Python for ML applications
Job Responsibility
Job Responsibility
  • Design and implement end-to-end ML solutions from experimentation to production
  • Build scalable ML pipelines and infrastructure
  • Optimize model performance, efficiency, and reliability
  • Write clean, maintainable, production-quality code
  • Conduct rigorous experimentation and model evaluation
  • Troubleshoot and resolve complex technical challenges
  • Mentor junior and mid-level ML engineers
  • Conduct code reviews and provide constructive feedback
  • Share knowledge through documentation, presentations, and workshops
  • Collaborate with cross-functional teams (DevOps, Data Engineering, SAs)
What we offer
What we offer
  • Long-term B2B collaboration
  • Fully remote setup
  • A budget for your medical insurance
  • Paid sick leave, vacation, public holidays
  • Continuous learning support, including unlimited AWS certification sponsorship
Read More
Arrow Right

Senior ML Engineer (GenAI)

As a Senior ML Engineer at Provectus, you'll be responsible for designing, devel...
Location
Location
Colombia , Medellín; Bogotá; Cali; Barranquilla; Bucaramanga
Salary
Salary:
Not provided
provectus.com Logo
Provectus
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • ML Fundamentals: supervised, unsupervised, and reinforcement learning
  • Model Development: feature engineering, model training, evaluation, hyperparameter tuning, and validation
  • ML Frameworks: classical ML libraries, TensorFlow, PyTorch, or similar frameworks
  • Deep Learning: CNNs, RNNs, Transformers
  • LLM Applications: Experience building production LLM-based applications
  • Prompt Engineering: Ability to design effective prompts and chain-of-thought strategies
  • RAG Systems: Experience building retrieval-augmented generation architectures
  • Vector Databases: Familiarity with embedding models and vector search
  • LLM Evaluation: Experience with evaluation metrics and techniques for LLM outputs
  • Python: Advanced proficiency in Python for ML applications
Job Responsibility
Job Responsibility
  • Design and implement end-to-end ML solutions from experimentation to production
  • Build scalable ML pipelines and infrastructure
  • Optimize model performance, efficiency, and reliability
  • Write clean, maintainable, production-quality code
  • Conduct rigorous experimentation and model evaluation
  • Troubleshoot and resolve complex technical challenges
  • Mentor junior and mid-level ML engineers
  • Conduct code reviews and provide constructive feedback
  • Share knowledge through documentation, presentations, and workshops
  • Collaborate with cross-functional teams (DevOps, Data Engineering, SAs)
Read More
Arrow Right