{"id":1622746,"url":"https://alion.io/job/exl-machine-learning-engineer","title":"Machine Learning Engineer","company":{"id":38016,"name":"EXL","domain":"exlservice.com","url":"https://alion.io/company/exl","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":80,"open_postings":57,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-10-06T05:45:30Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Dublin, Ireland"],"countries":["IE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":80000,"max_usd":164000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":8},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"Airflow","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"CI/CD","optional":false},{"name":"Embeddings","optional":false},{"name":"Feature Store","optional":false},{"name":"Hallucination","optional":false},{"name":"Kubeflow","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"MySQL","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenSearch","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Weights & Biases","optional":false},{"name":"Agile","optional":true},{"name":"Docker","optional":true},{"name":"GraphQL","optional":true},{"name":"Kubernetes","optional":true},{"name":"Rest API","optional":true},{"name":"Scrum","optional":true}],"status":"live","first_seen_at":"2026-08-19T18:45:27Z","employer_posted_date":"2026-08-19","last_verified_at":"2026-10-06T21:00:18Z","board_verified":true,"closed_at":null,"days_open":48,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":48},"description":"EXL (NASDAQ: EXLS) is a global data and artificial intelligence (\"AI\") company that offers services and solutions to reinvent client business models, drive better outcomes and unlock growth with speed. EXL harnesses the power of data, AI, and deep industry knowledge to transform businesses, including the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect.\nWe are headquartered in New York and have more than 60,000 employees spanning six continents. For more information, visit www.exlservice.com.\nRole Title: Machine Learning Engineer\nBU/Segment: Digital\nLocation: Dublin, Republic of Ireland (Flexible hybrid working)\nEmployment Type: Permanent\nSummary of the role:\nEXL Digital is looking for an experienced Machine Learning Engineer to join our team. At EXL, we believe there is always a better way. We look deeper, we find it, and we make it happen. We've built a culture founded on core values of innovation, collaboration, excellence, integrity, and respect.\nIn this role, you will design, build, and operate machine learning and GenAI systems that power our products and client solutions. You'll work with product, engineering, and client stakeholders to identify high-impact opportunities, rapidly prototype solutions, and harden them into scalable, secure, and cost-effective production systems. You'll also help set ML engineering standards across the team, from data quality and evaluation rigor to MLOps and responsible AI practices.\nAs part of your duties, you will be responsible for:\nDesign, build, and deploy machine learning models and GenAI solutions that solve real business problems, from problem framing and data exploration through production deployment and monitoring.\nDevelop end-to-end ML pipelines covering data ingestion, feature engineering, training, evaluation, deployment, and retraining, using orchestration tools such as Apache Airflow.\nBuild and productionize GenAI applications, including LLM integration, prompt engineering, RAG (retrieval-augmented generation) pipelines, embeddings, vector databases, and agentic workflows.\nFine-tune, evaluate, and optimize models (classical ML, deep learning, and LLMs) for accuracy, latency, and cost.\nDeploy and operate models in production on AWS (or comparable cloud platforms) using services such as SageMaker, Bedrock, Lambda, and containerized inference.\nImplement MLOps best practices: experiment tracking, model versioning, CI/CD for ML, automated testing, monitoring for drift and performance degradation.\nWork with large, messy, real-world datasets: design data pipelines, ensure data quality, and build robust feature stores in partnership with data engineering.\nEstablish evaluation frameworks for both traditional models (precision/recall, AUC, calibration) and LLM-based systems (grounding, hallucination rates, task success metrics).\nEmbed responsible AI practices: fairness, explainability, privacy, and security, into model development and deployment.\nCollaborate with product managers, architects, and client stakeholders to translate business requirements into ML solutions with measurable impact.\nWrite clean, well-tested, production-quality code and participate in design and code reviews.\nBuild proof-of-concepts to validate ML/GenAI approaches quickly, and harden successful experiments into production systems.\nMentor junior engineers and data scientists on ML engineering best practices.\nStay current with the rapidly evolving ML/GenAI landscape and recommend adoption of new models, frameworks, and techniques where they add business value.\nQualifications and experience we consider to be essential for the role:\nMinimum 5 years of software or data engineering experience, with at least 3 years building and deploying machine learning models in production.\nStrong programming skills in Python and hands-on experience with ML frameworks such as scikit-learn, PyTorch, or TensorFlow.\nPractical experience building GenAI/LLM applications: prompt engineering, RAG pipelines, embeddings, vector databases (e.g., pgvector, Pinecone, OpenSearch), and LLM APIs (OpenAI, Anthropic, Bedrock).\nSolid grounding in ML fundamentals: supervised/unsupervised learning, feature engineering, model evaluation, and error analysis.\nExperience deploying and operating models on AWS (or comparable cloud): SageMaker, Bedrock, Lambda, ECS/EKS, or equivalent services.\nWorking knowledge of MLOps tooling: experiment tracking (MLflow, Weights & Biases), model registries, pipeline orchestration (Apache Airflow, Kubeflow, or Step Functions), and monitoring.\nStrong data skills: SQL, workflow orchestration with Apache Airflow, and experience with relational (PostgreSQL, MySQL) and NoSQL data stores; exposure to Spark or similar big-data tools is a plus.\nExperience exposing models as services: REST/GraphQL APIs, batch and real-time inference, and integration with backend applications.\nSolid software engineering fundamentals: version control, testing, CI/CD, containers (Docker/Kubernetes), and code review practices.\nUnderstanding of responsible AI concepts: bias, explainability, privacy, and security considerations in ML systems.\nExperience working in Agile/SCRUM environments and delivering iteratively.\nExcellent communication skills, with the ability to explain models, trade-offs, and results to both technical and non-technical audiences.\nAbility to work with stakeholders across multiple geographies.\nAs part of a leading global Data and AI company, you can look forward to:\nA competitive salary with a generous bonus, private healthcare, life assurance at 4 x your annual salary, income protection insurance, and a rewarding pension.\nAt EXL, we are committed to providing our employees with the tools and resources they need to succeed and excel in their careers. We offer a wide range of professional and personal development opportunities. We also support a range of learning initiatives that allow our employees to build on their existing skills and knowledge. From online courses to seminars and workshops, our employees have the opportunity to enhance their skills and stay up to date with the latest trends and technologies.\nAs an Equal Opportunity Employer, EXL is committed to diversity. Our company does not discriminate based on race, religion, colour, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, age, or disability status.\nAtEXL, we offer a flexible hybrid working model that allows employees to live a balanced, healthy lifestyle while strengthening our culture of collaboration.\nTo be considered for this role, you must already be eligible to work in the Republic of Ireland.","description_format":"text","description_chars":6841,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Hybrid work"],"hiring_locations":[{"name":"Ireland","iso":"IE","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-01T20:51:11Z"}],"visa":[],"liveness":{"score":4,"band":"cold","label":"Long shot","p_open":1,"p_active":0.161,"p_room":0.28,"age_days":47,"expected_fill_days":6,"reasons":["conf:1","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-06T05:45:30Z"},"pay":null,"html_url":"https://alion.io/job/exl-machine-learning-engineer","json_url":"https://alion.io/job/exl-machine-learning-engineer.json","meta":{"generated_at":"2026-10-06T22:07:15Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":2289,"day_limit":5000,"remaining_today":2711,"minute_limit":60,"resets_at":"2026-10-07T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":38016},"rest":"https://alion.io/mcp/rest/get_company?id=38016"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fexl-machine-learning-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fexl-machine-learning-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fexl-machine-learning-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/exl-machine-learning-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fexl-machine-learning-engineer"}]}