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Machine Learning Manager
Grupo Dice Seguridad
Abu Dhabi, UAE
Full Time
Manager
Remote
1 weeks ago
Machine LearningPythonTensorFlowPyTorchScikit learnMLflow
Free
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Machine LearningPythonTensorFlow
About the Role
We are hiring a Machine Learning Manager to lead the development, deployment, and optimization of ML solutions. The role requires 7+ years of ML experience and 3+ years managing teams.
Key Skills for This Role
Machine LearningPythonTensorFlowPyTorchScikit learnMLflow
Responsibilities
- Develop and execute machine learning strategies aligned with organizational objectives, product roadmaps, and business priorities
- Lead the design, development, deployment, monitoring, and continuous improvement of machine learning models and AI powered applications across multiple business domains
- Collaborate with product management, software engineering, data engineering, platform engineering, analytics, and business stakeholders to identify high impact machine learning opportunities
- Establish best practices for machine learning development, feature engineering, model training, evaluation, deployment, monitoring, versioning, and governance
- Oversee the implementation of MLOps pipelines, model lifecycle management, automated retraining, experimentation frameworks, and CI/CD for machine learning workloads
- Ensure machine learning models meet performance, scalability, reliability, security, fairness, explainability, and regulatory compliance requirements
- Monitor key performance indicators (KPIs) including model accuracy, precision, recall, latency, inference performance, deployment success, business impact, and operational efficiency
- Drive research and evaluation of emerging AI technologies, large language models (LLMs), generative AI, deep learning frameworks, and advanced machine learning methodologies where appropriate
- Lead model validation, bias assessment, risk management, root cause analysis, and continuous optimization initiatives to improve model quality and business outcomes
- Manage machine learning infrastructure, cloud resources, budgets, technology investments, vendor relationships, and project roadmaps to support organizational objectives
- Prepare technical reports, executive dashboards, model performance analyses, and strategic recommendations for senior leadership
- Lead, mentor, and develop machine learning engineers, data scientists, MLOps engineers, and AI specialists while fostering a culture of innovation, collaboration, technical excellence, and continuous improvement
Requirements
- Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, Mathematics, Statistics, or a related field preferred
- Master's degree or Ph.D. in Artificial Intelligence, Machine Learning, Computer Science, Data Science, or a related discipline is advantageous
- Professional certifications in AWS Machine Learning, Google Professional Machine Learning Engineer, Microsoft Azure AI Engineer, TensorFlow, or equivalent are advantageous
- 7+ years of experience in machine learning, artificial intelligence, data science, or advanced analytics roles
- 3+ years of experience managing machine learning teams, AI initiatives, or cross functional engineering projects preferred
- Strong understanding of supervised and unsupervised learning, deep learning, natural language processing (NLP), computer vision, recommendation systems, reinforcement learning, and statistical modeling
- Experience with Python, TensorFlow, PyTorch, Scikit learn, MLflow, Kubeflow, Spark, SQL, cloud platforms (AWS, Azure, or GCP), Docker, Kubernetes, and modern MLOps practices
- Familiarity with generative AI, large language models (LLMs), vector databases, retrieval augmented generation (RAG), prompt engineering, and AI governance frameworks is advantageous
- Strong analytical, leadership, strategic thinking, project management, and problem solving skills
- Excellent communication, stakeholder management, mentoring, and cross functional collaboration abilities
- Ability to translate complex machine learning solutions into measurable business outcomes while balancing innovation, scalability, reliability, and responsible AI practices
- Ability to work independently in a remote environment
Full Job Posting
About Us
- We are a technology driven organization committed to leveraging artificial intelligence and machine learning to build innovative, data driven solutions that enhance customer experiences, optimize business operations, and accelerate sustainable growth.
- Our teams collaborate across engineering, data science, product, analytics, platform, and business functions to develop intelligent systems that deliver measurable business value.
The Role
- We are seeking an experienced Machine Learning Manager to lead the development, deployment, and optimization of machine learning solutions across the organization.
- The ideal candidate will oversee machine learning strategy, guide technical teams, establish best practices, and collaborate with cross functional stakeholders to deliver scalable AI powered products and data driven business outcomes.
Key Responsibilities
- Develop and execute machine learning strategies aligned with organizational objectives, product roadmaps, and business priorities
- Lead the design, development, deployment, monitoring, and continuous improvement of machine learning models and AI powered applications across multiple business domains
- Collaborate with product management, software engineering, data engineering, platform engineering, analytics, and business stakeholders to identify high impact machine learning opportunities
- Establish best practices for machine learning development, feature engineering, model training, evaluation, deployment, monitoring, versioning, and governance
- Oversee the implementation of MLOps pipelines, model lifecycle management, automated retraining, experimentation frameworks, and CI/CD for machine learning workloads
- Ensure machine learning models meet performance, scalability, reliability, security, fairness, explainability, and regulatory compliance requirements
- Monitor key performance indicators (KPIs) including model accuracy, precision, recall, latency, inference performance, deployment success, business impact, and operational efficiency
- Drive research and evaluation of emerging AI technologies, large language models (LLMs), generative AI, deep learning frameworks, and advanced machine learning methodologies where appropriate
- Lead model validation, bias assessment, risk management, root cause analysis, and continuous optimization initiatives to improve model quality and business outcomes
- Manage machine learning infrastructure, cloud resources, budgets, technology investments, vendor relationships, and project roadmaps to support organizational objectives
- Prepare technical reports, executive dashboards, model performance analyses, and strategic recommendations for senior leadership
- Lead, mentor, and develop machine learning engineers, data scientists, MLOps engineers, and AI specialists while fostering a culture of innovation, collaboration, technical excellence, and continuous improvement
Requirements
- Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, Mathematics, Statistics, or a related field preferred
- Master's degree or Ph.D. in Artificial Intelligence, Machine Learning, Computer Science, Data Science, or a related discipline is advantageous
- Professional certifications in AWS Machine Learning, Google Professional Machine Learning Engineer, Microsoft Azure AI Engineer, TensorFlow, or equivalent are advantageous
- 7+ years of experience in machine learning, artificial intelligence, data science, or advanced analytics roles
- 3+ years of experience managing machine learning teams, AI initiatives, or cross functional engineering projects preferred
- Strong understanding of supervised and unsupervised learning, deep learning, natural language processing (NLP), computer vision, recommendation systems, reinforcement learning, and statistical modeling
- Experience with Python, TensorFlow, PyTorch, Scikit learn, MLflow, Kubeflow, Spark, SQL, cloud platforms (AWS, Azure, or GCP), Docker, Kubernetes, and modern MLOps practices
- Familiarity with generative AI, large language models (LLMs), vector databases, retrieval augmented generation (RAG), prompt engineering, and AI governance frameworks is advantageous
- Strong analytical, leadership, strategic thinking, project management, and problem solving skills
- Excellent communication, stakeholder management, mentoring, and cross functional collaboration abilities
- Ability to translate complex machine learning solutions into measurable business outcomes while balancing innovation, scalability, reliability, and responsible AI practices
- Ability to work independently in a remote environment
What We Offer
- Fully remote work opportunity within the United Arab Emirates
- Competitive compensation package
- Professional development and AI leadership growth opportunities
- Exposure to cutting edge artificial intelligence, generative AI, cloud native machine learning platforms, and enterprise digital transformation initiatives
- Flexible and collaborative work environment
- Supportive culture focused on innovation, technical excellence, responsible AI, collaboration, and continuous improvement
- Opportunity to lead enterprise scale machine learning initiatives that drive innovation and competitive advantage
- Clear career progression within machine learning leadership, artificial intelligence, data science management, engineering leadership, and executive technology functions
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