Senior AI/ML Engineer

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Senior AI/ML Engineer

Abacus

Location

Lahore, Pakistan

Experience

Senior

Posted

Jul 18, 2026

Apply by

August 17, 2026

Applicants

0

Early applicantEasy applyFull-timeWork from Office

Job Description

Role Summary Designs, develops, deploys, and optimises Artificial Intelligence (AI) and Machine Learning (ML) solutions within the Software Engineering Centre of Excellence (CoE). Works closely with software engineering squads, data teams, architects, DevOps, and business stakeholders to build scalable AI-enabled products, intelligent automation capabilities, predictive models, and advanced analytics solutions that support business and customer outcomes. Responsibilities - Design, develop, train, test, and deploy machine learning and AI models for enterprise and customer-facing solutions - Collaborate with software engineering squads, data engineers, architects, and product owners to integrate AI capabilities into digital products and platforms - Build scalable AI/ML pipelines and support operationalisation of models within production environments - Develop and optimise models for predictive analytics, automation, recommendation engines, NLP, GenAI, and intelligent decisioning solutions - Work with large structured and unstructured datasets to support AI solution development - Support AI platform engineering, model governance, monitoring, and continuous improvement practices - Implement MLOps and DevOps best practices for model deployment, testing, monitoring, and lifecycle management - Evaluate and recommend AI frameworks, tools, accelerators, and emerging technologies - Support development of reusable AI engineering assets, accelerators, and standards within the CoE - Collaborate with security, governance, and compliance teams to ensure responsible AI practices and data governance compliance - Support technical solution design, estimation, and implementation planning for AI-enabled initiatives - Provide technical leadership and mentorship to engineering teams on AI/ML engineering practices - Contribute to continuous improvement, innovation initiatives, and AI capability development within the Software Engineering CoE Qualification & Experience - Bachelor's degree (BA/BS) in Computer Science, Data Science, Artificial Intelligence, Mathematics, Engineering, or related field preferred - At least 8–10 years of experience in software engineering, AI, machine learning, or data engineering environments - At least 5 years of hands-on experience developing and deploying AI/ML solutions in enterprise environments - Experience with machine learning frameworks and tools such as TensorFlow, PyTorch, Scikit-learn, MLflow, LangChain, or similar technologies - Experience with cloud AI platforms and services such as AWS, Azure, or Google Cloud - Experience with MLOps, CI/CD pipelines, containerisation, and cloud-native engineering practices - Strong understanding of software engineering principles, APIs, microservices, and scalable system design - Experience working within Agile software delivery teams Preferred Skills - AI and machine learning model development - Generative AI and Large Language Model (LLM) integration - Natural Language Processing (NLP) - Predictive analytics and data modelling - MLOps and AI operationalisation - Python, SQL, and modern programming frameworks - Cloud engineering and distributed systems - API and microservices integration - Analytical and problem-solving capability - Strong stakeholder engagement and communication skills - Ability to simplify technical concepts for business stakeholders - Process improvement and innovation mindset - Ability to work independently and across multiple agile squads - Good communication (written and oral) and interpersonal skills - Good organisational, multi-tasking, and time-management skills

Key Responsibilities

  • Design, develop, train, test, and deploy machine learning and AI models for enterprise and customer-facing solutions
  • Collaborate with software engineering squads, data engineers, architects, and product owners to integrate AI capabilities into digital products
  • Build scalable AI/ML pipelines and support operationalisation of models within production environments
  • Develop and optimise models for predictive analytics, automation, recommendation engines, NLP, GenAI, and intelligent decisioning solutions
  • Work with large structured and unstructured datasets to support AI solution development
  • Support AI platform engineering, model governance, monitoring, and continuous improvement practices
  • Implement MLOps and DevOps best practices for model deployment, testing, monitoring, and lifecycle management
  • Evaluate and recommend AI frameworks, tools, accelerators, and emerging technologies
  • Support development of reusable AI engineering assets, accelerators, and standards within the CoE
  • Collaborate with security, governance, and compliance teams to ensure responsible AI practices and data governance compliance
  • Support technical solution design, estimation, and implementation planning for AI-enabled initiatives
  • Provide technical leadership and mentorship to engineering teams on AI/ML engineering practices
  • Contribute to continuous improvement, innovation initiatives, and AI capability development within the Software Engineering CoE

Skills Required

TensorFlowPyTorchScikit-learnMLflowLangChainAWSAzureGoogle CloudMLOpsCI/CDContainerisationCloud-native engineeringSoftware engineering principlesAPIsMicroservicesScalable system designAgileTechnical leadershipMentorshipCollaborationCommunicationGenerative AILarge Language Model (LLM) integrationNatural Language Processing (NLP)Predictive analyticsData modellingAI operationalisationPythonSQLCloud engineeringDistributed systemsAPI integrationMicroservices integrationAnalytical capabilityProblem-solvingStakeholder engagementCommunication skillsAbility to simplify technical conceptsProcess improvement mindsetInnovation mindsetAbility to work independentlyMulti-taskingTime-managementInterpersonal skillsOrganisational skills

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