Account Executive- Cybersecurity

Senior Machine Learning Engineer (Production & MLOps Focus)

 IIAD / SAD / LAD Artificial Intelligence Engineer

Principal Applied Data Scientist

Director, Data Science

Solution Engineer AI

Responsibilities: <ul><li>Work closely with internal stakeholders like Channel team, Account team and Industry partners individually to build a successful pipeline to meet and exceed your individual sales quota</li><li>Identify new business opportunities whilst establishing, developing and maintaining relationships up to executive-levels within your assigned portfolio</li><li>Network within the client’s business and influence key decision makers, typically at C-level</li><li>Act as Clients ambassador within specific client accounts</li><li>Articulate and promote the company’s security&nbsp;value proposition and services to become a trusted advisor within your customer base</li><li>Identify new business opportunities and prepare detailed account development plans, engagement strategies and targets for each account within your assigned portfolio</li><li>Take control of opportunities and accurately forecast business objectives and outcomes. Follow MEDDPICC.</li></ul> Requirements: <ul><li>Min 10 years of experience selling cybersecurity solutions in Delhi/NCR region.</li><li>Proven successful track record in a similar role selling high technology products to Enterprise customers.</li><li>Ability to network multiple levels within an account up to C-Level.</li><li>Ability to create and deliver value propositions.</li><li>Proven sales track record.</li><li>Excellent verbal, written and presentation skills.</li></ul>

Responsibilities: <ul><li>Design, deploy, and maintain production-ready ML models and pipelines for real-world applications.&nbsp;</li><li>Build and scale ML pipelines using Vertex AI Pipelines, Kubeflow, Airflow, and manage infra-as-code with Terraform/Helm.&nbsp;</li><li>Implement automated retraining, drift detection, and re-deployment of ML models.&nbsp;</li><li>Develop CI/CD workflows (GitHub Actions, GitLab CI, Jenkins) tailored for ML.&nbsp;</li><li>Implement model monitoring, observability, and alerting across accuracy, latency, and cost.&nbsp;</li><li>Integrate and manage feature stores, knowledge graphs, and vector databases for advanced ML/RAG use cases.&nbsp;</li><li>Ensure pipelines are secure, compliant, and cost-optimized.&nbsp;&nbsp;</li><li>Drive adoption of MLOps best practices: develop and maintain workflows to ensure reproducibility, versioning, lineage tracking, governance .&nbsp;</li><li>Mentor junior engineers and contribute to long-term ML platform architecture design and technical roadmap.&nbsp;</li><li>Stay current with the latest ML research and apply new tools pragmatically to production systems.&nbsp;</li><li>Collaborate with product managers, DS, and engineers to translate business problems into reliable ML systems.&nbsp;</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field (PhD is a plus).&nbsp;</li><li>5+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems.&nbsp;</li><li>Strong foundations in data structures, algorithms, and distributed systems.&nbsp;</li><li>Proficient in Python (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) and SQL.&nbsp;</li><li>Hands-on experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML).&nbsp;</li><li>Experience with containerization (Docker, Kubernetes) and orchestration (Airflow, TFX, Kubeflow).&nbsp;</li><li>Familiarity with CI/CD pipelines, infrastructure-as-code (Terraform/Helm), and configuration management.&nbsp;</li><li>Experience with big data and streaming technologies (Spark, Flink, Kafka, Hive, Hadoop).&nbsp;</li><li>Practical exposure to model observability tools (Prometheus, Grafana, EvidentlyAI) and governance (WatsonX)&nbsp;</li><li>Strong understanding of statistical methods, ML algorithms, and deep learning architectures.&nbsp;</li></ul>

Responsibilities: <ul><li>Work closely with internal stakeholders like Channel team, Account team and Industry partners individually to build a successful pipeline to meet and exceed your individual sales quota</li><li>Identify new business opportunities whilst establishing, developing and maintaining relationships up to executive-levels within your assigned portfolio</li><li>Network within the client’s business and influence key decision makers, typically at C-level</li><li>Act as Clients ambassador within specific client accounts</li><li>Articulate and promote the company’s security&nbsp;&nbsp;value proposition and services to become a trusted advisor within your customer base</li><li>Identify new business opportunities and prepare detailed account development plans, engagement strategies and targets for each account within your assigned portfolio</li><li>Take control of opportunities and accurately forecast business objectives and outcomes. Follow MEDDPICC</li></ul> Minimum Qualifications – <ul><li>Min 10 years of experience selling cybersecurity solutions in Delhi/NCR region</li><li>Proven successful track record in a similar role selling high technology products to Enterprise customers</li><li>Ability to network multiple levels within an account up to C-Level</li><li>Ability to create and deliver value propositions</li><li>Proven sales track record</li><li>Excellent verbal, written and presentation skills</li></ul>

Responsibilities: Agentic AI Development:&nbsp;&nbsp; <ul><li>Design, build, and deploy agentic AI systems using frameworks such as LangChain, Lang Graph, and related libraries.&nbsp;&nbsp;</li><li>Develop and deploy multi-agent systems capable of autonomous decision-making, reasoning, planning, and collaboration.&nbsp;</li></ul> RAG Pipelines:&nbsp; <ul><li>Implement and optimize retrieval-augmented generation (RAG) systems, ensuring agents can access and incorporate external knowledge sources for grounded, accurate responses.&nbsp;</li></ul> LLM Engineering:&nbsp; <ul><li>Fine-tune and prompt-engineer LLMs for task-specific reasoning, planning, and dynamic adaptation.&nbsp;</li><li>Work with LLM/SLM APIs, embeddings, and advanced generative AI techniques.&nbsp;</li></ul> Enterprise AI Platform:&nbsp; <ul><li>Lead the development of enterprise-grade AI platforms integrating LLMs, RAG, embeddings, and agentic AI protocols.&nbsp;</li><li>Implement and standardize Model Context Protocol (MCP) for consistent context management across models and agents.&nbsp;</li></ul> MLOps &amp; Observability:&nbsp; <ul><li>Establish and enforce best practices for MLOps, monitoring, and observability, ensuring scalable and maintainable AI solutions.&nbsp;</li><li>Applied AI Prototyping:&nbsp;</li></ul> Rapidly prototype, experiment, and iterate to improve AI agent capabilities.&nbsp; Collaboration &amp; Research:&nbsp; <ul><li>Participate in the full research cycle: literature review, data exploration, experimentation, and presentation of findings.&nbsp;</li><li>Collaborate effectively with other engineers, researchers, and data scientists.&nbsp;</li><li>Contribute to the documentation and standardization of technical code and practices.&nbsp;</li></ul>&nbsp;Requirements: <ul><li>Bachelor’s degree in Computer Science, Engineering, or a related quantitative field. Master’s or Ph.D. is a strong plus.&nbsp;</li><li>5+ years overall experience in software development, data science, or machine learning.&nbsp;</li><li>1+ year of hands-on experience developing AI applications with LLMs and systems such as retrieval-based methods, fine-tuning, or agent-based architectures.&nbsp;</li><li>1+ year of experience with frameworks like LangChain, LlamaIndex, OpenAI, or similar tools.&nbsp;</li></ul>

Role Description: <ul><li>Develop and own the data science roadmap that aligns with our client business goals.</li><li>Define success metrics and oversee the entire lifecycle of data initiatives from concept to production deployment.</li><li>Architect, develop, and deploy state-of-the-art machine learning models.</li><li>Champion best practices in model development, validation, and monitoring in production environments.</li><li>Partner with product, engineering, and business teams to translate business requirements into data-driven solutions.</li></ul> Responsibilities: <ul><li>Provide technical leadership and mentor the data science team.</li><li>Provide technical leadership and mentor the data science team.</li><li>Architect and provide production monitoring and support for our client ML services.</li><li>Stay ahead of industry trends by continuously evaluating emerging technologies and methodologies in data science and machine learning.</li><li>Represent our client technical excellence through publications, presentations, and participation in industry events.</li></ul> Requirements: <ul><li>10+ years of professional experience in data science with a proven track record in building and supporting production grade ML systems.</li><li>Must be highly proficient in Python with hands-on experience in machine learning frameworks (e.g., TensorFlow, PyTorch).</li><li>Experience working with large-scale datasets and distributed computing platforms like GCP.</li><li>Strong understanding of ML lifecycle and MLOps practices.</li><li>Experience with monitoring tools like Prometheus, Grafana and logging systems e.g. ELK stack.</li></ul>

Responsibilities: Strategic Leadership:&nbsp; <ul><li>Define and execute the data science vision and roadmap aligned with business objectives and technological advancement opportunities.</li></ul> Team Management:&nbsp; <ul><li>Build, lead, and mentor a high-performing team of data scientists, fostering a culture of innovation, collaboration, and continuous learning.</li></ul> Advanced Research Direction:&nbsp; <ul><li>Direct cutting-edge research initiatives in NLP, LLMs, and other emerging AI technologies to maintain competitive advantage.</li></ul> Machine Learning and AI Solutions:&nbsp; <ul><li>Lead the development and implementation of machine learning algorithms and AI solutions to solve complex business problems.</li></ul> Data Collection and Preparation:&nbsp; <ul><li>Establish protocols for collecting, cleaning, and preprocessing large datasets, ensuring data quality and reliability.</li></ul> Data Visualization Strategy:&nbsp; <ul><li>Guide the creation of informative and compelling data visualizations to communicate results and insights to stakeholders effectively.</li></ul> Cross-functional Collaboration:&nbsp; <ul><li>Partner with executive leadership and cross-functional teams to identify strategic opportunities and address business challenges.</li></ul> Model Deployment and MLOps:&nbsp; <ul><li>Oversee the deployment of machine learning models into pro duction environments, ensuring scalability and reliability.</li></ul> Documentation Standards:&nbsp; <ul><li>Establish comprehensive documentation standards for projects, models, and code for knowledge sharing and reproducibility.</li></ul> Budget and Resource Management:&nbsp; <ul><li>Manage departmental budget, resource allocation, and infrastructure needs for data science operations.</li></ul> Ethical AI Governance:&nbsp; <ul><li>Develop and enforce ethical guidelines and best practices for AI development and deployment.</li></ul> Requirements: <ul><li>Bachelors, Masters or Ph.D. in Data Science, Computer Science, Statistics, or a related field; MBA or additional business education is a plus.</li><li>10+ years of progressive experience in data science, machine learning, or AI, with at least 8 years in leadership positions.</li><li>Demonstrated experience in managing and scaling data science teams of 15+ professionals.</li><li>Proven record of delivering high-impact AI and ML solutions that have driven significant business value.</li><li>Deep expertise with generative AI models and techniques (e.g., LLMs, GANs) for content generation and their practical applications.</li><li>Advanced knowledge of statistical analysis, machine learning algorithms, and data manipulation techniques at enterprise scale.</li><li>Experience in setting technical direction and implementing MLOps practices for model deployment and monitoring.</li><li>Strong business acumen with the ability to translate complex technical concepts into business value.</li><li>Excellent communication and leadership skills, with experience presenting to executive leadership.</li><li>Experience working in a global or multicultural environment.</li><li>Record of successful collaboration with product, engineering, and business teams.</li><li>Proficiency in multiple programming languages relevant to data science (Python, R, etc.) and big data technologies.</li></ul>

Responsibilities: <ul><li>Lead and manage strategic sales opportunities within the AI Infrastructure and Data Centre space.</li><li>Identify and develop new business opportunities through proactive prospecting and relationship building.</li><li>Collaborate closely with customers and partners to define and align strategic technology visions and business outcomes.</li><li>Understand customer-specific needs and tailor sales strategies to address those priorities effectively.</li><li>Maintain deep knowledge of data centre technologies, with a strong focus on AI-related infrastructure solutions.</li><li>Drive sales growth in a competitive environment by executing a results-oriented business development strategy.</li><li>Build and maintain strong, trusted relationships with key technology leaders and decision-makers across the industry.</li><li>Represent and advocate for as a leader in AI Infrastructure within the market and among strategic accounts.</li></ul> Requirements: Minimum Qualifications&nbsp; <ul><li>7+ years of technology-related sales or account management experience with a focus on business development and new technology incubation.&nbsp;</li><li>Experience growing revenue for new innovative technology-based solutions.&nbsp;</li><li>Experience in understanding business challenges when deploying data centre infrastructure at scale, including AI Infrastructure.&nbsp;&nbsp;</li><li>Proven track record of working cross-functionally with Sales, Presales and Marketing to develop and launch new data centre infrastructure offers.&nbsp;</li></ul> Preferred Qualifications: <ul><li>Bachelor’s degree or equivalent experience in Business, Computer Science, Engineering, or a related field; advanced degree is a plus.&nbsp;</li><li>Excellent verbal and written communication skills.&nbsp;</li><li>Experience working within technology incubate teams to grow market share at an accelerated rate.&nbsp;</li><li>Sales Experience associated with deep learning, data science and AI Infrastructure.&nbsp;</li><li>Sales experience with Data Centre relevant technology, such as storage, network, platform, server, security and cloud.&nbsp;</li></ul>

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7 mlops Jobs found

Account Executive- Cybersecurity

Senior Machine Learning Engineer (Production & MLOps Focus)

Account Executive- Cybersecurity

IIAD / SAD / LAD Artificial Intelligence Engineer

Principal Applied Data Scientist

Director, Data Science

Solution Engineer AI

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Account Executive- Cybersecurity

Senior Machine Learning Engineer (Production & MLOps Focus)

Account Executive- Cybersecurity

IIAD / SAD / LAD Artificial Intelligence Engineer

Principal Applied Data Scientist

Director, Data Science

Solution Engineer AI

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

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