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Key Responsibilities

• Define AI-driven growth and marketing strategy

• Lead AI adoption across paid media, CRM, and automation platforms

• Drive predictive modeling for customer acquisition and retention

• Partner with executive leadership on revenue growth initiatives

• Manage senior marketing and AI teams

  Skills & Qualifications

  • 10–15+ years in AI, marketing analytics, or growth leadership

  • Strong background in AI, ML, and customer data platforms

  • Experience with AI-powered ad platforms and MarTech tools

  • Proven leadership and business growth track record

  • Benefits

    • Salary up to $200K

    • Executive bonuses

    • Flexible work model

    • High-impact leadership role

We are seeking a highly experienced Senior AI Manager to lead our Data Science and AI-driven Marketing initiatives. This role requires strong leadership, advanced analytics expertise, and hands-on experience in applying AI to business growth, customer acquisition, and marketing automation.

Key Responsibilities

AI & Data Science Leadership

• Lead end-to-end AI and data science strategy across marketing and business teams

• Design and deploy machine learning models for prediction, segmentation, and personalization

• Oversee data pipelines, model training, validation, and deployment

• Translate complex data insights into business-driven decisions

• AI-Powered Marketing Strategy

  • Drive AI-based marketing solutions (customer targeting, churn prediction, recommendation systems)

  • Implement AI tools for performance marketing, lead scoring, and attribution modeling

  • Optimize campaigns using predictive analytics and real-time data insights

  • Collaborate with marketing teams to improve ROI using AI automation

  Team & Stakeholder Management

  • Manage and mentor data scientists, ML engineers, and marketing analysts

  • Collaborate with leadership, product, sales, and marketing teams

  • Present AI strategies and insights to senior stakeholders

    Required Skills & Qualifications

    Technical Skills

    • Strong expertise in Machine Learning, Deep Learning, and Statistical Modeling

    • Proficiency in Python, SQL, R, and data visualization tools

    • Experience with AI marketing platforms, CRM analytics, and automation tools

    • Hands-on experience with cloud platforms (AWS, Azure, or GCP)

    • Knowledge of GenAI, NLP, recommendation engines, and predictive analytics

    Marketing & Business Skills

    • Deep understanding of digital marketing, performance marketing, and customer analytics

    • Experience applying AI to SEO, paid ads, email automation, and customer journey optimization

    • Strong business acumen with ROI-focused decision-making

      Compensation & Benefits

      • Salary up to $200,000 annually

      • Performance-based bonuses

      • Health insurance & retirement benefits

      • Flexible work environment (Remote/Hybrid)

      • Opportunity to lead high-impact AI transformation projects

Job Summary

We are seeking an innovative and highly skilled Generative AI Scientist to research, develop, and deploy cutting-edge AI solutions powered by Large Language Models (LLMs), multimodal AI systems, and generative machine learning technologies. The successful candidate will design advanced AI models that generate text, images, code, and other forms of content while driving business innovation and automation.

Key Responsibilities

• Research, develop, and optimize Generative AI models and applications.
• Fine-tune and evaluate Large Language Models (LLMs) for domain-specific use cases.
• Design and implement Retrieval-Augmented Generation (RAG) systems to improve AI accuracy and reliability.
• Develop AI-powered solutions for content generation, conversational AI, document intelligence, and decision support systems.
• Create and maintain prompt engineering frameworks and AI evaluation methodologies.
• Collaborate with data scientists, software engineers, and business stakeholders to deliver AI-driven products.
• Conduct model benchmarking, performance analysis, and continuous improvement initiatives.
• Implement responsible AI practices, including bias detection, safety monitoring, and model governance.
• Stay current with advancements in Generative AI, foundation models, multimodal AI, and emerging research.

Required Qualifications

• Bachelor's, Master's, or Ph.D. in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Mathematics, or a related field.
• Strong experience with machine learning, deep learning, and Generative AI technologies.
• Proficiency in Python and AI frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, and LangChain.
• Experience working with Large Language Models (GPT, Llama, Claude, Gemini, or similar models).
• Strong understanding of NLP, transformer architectures, embeddings, vector databases, and model evaluation techniques.
• Experience building scalable AI applications and APIs.

Preferred Qualifications

• Experience with multimodal AI models involving text, image, audio, and video generation.
• Knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with MLOps, CI/CD pipelines, Docker, and Kubernetes.
• Experience with reinforcement learning, agentic AI systems, and AI orchestration frameworks.
• Contributions to AI research, open-source projects, or published papers.

Technical Skills

• Generative AI
• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• Natural Language Processing (NLP)
• Deep Learning
• PyTorch / TensorFlow
• Hugging Face
• LangChain / LlamaIndex
• Vector Databases (Pinecone, Weaviate, ChromaDB)
• MLOps & Model Deployment
• Cloud Computing (AWS, Azure, GCP)

Success Metrics

• Development and deployment of high-performing Generative AI solutions.
• Improved AI response quality, accuracy, and reliability.
• Increased business efficiency through AI-driven automation.
• Successful implementation of scalable and secure AI systems.
• Contribution to innovation, research, and AI product development.

Job Description:

We are looking for a Site Reliability Engineer with a passion for astronomy and space technology to join our team. In this role, you will work closely with astronomers, astrophysicists, and data scientists to develop, deploy, and manage scalable infrastructure for astronomical data processing, observatory automation, and space research applications.

Key Responsibilities:

• Design, implement, and maintain CI/CD pipelines for astronomical software and data processing workflows.

• Manage and optimize cloud-based infrastructure (AWS, Azure, or Google Cloud) for large-scale space data storage and analysis.

• Automate deployment, scaling, and monitoring of telescope control systems, astrophysics simulations, and satellite operations.

• Collaborate with scientists and engineers to integrate DevOps best practices into astronomical research projects.

• Implement containerization and orchestration (Docker, Kubernetes) for astronomical data pipelines.

• Enhance system reliability, security, and performance for astronomical observatories and space missions.

• Develop and maintain infrastructure as code (Terraform, Ansible, or CloudFormation).

• Monitor and troubleshoot system performance and astronomical data processing jobs.

Requirements:

• Bachelor's or Master’s degree in Computer Science, Astronomy, Astrophysics, or related fields.

• 3+ years of experience in DevOps, SRE, or Cloud Engineering.

• Proficiency in Linux, Shell scripting, Python, or Golang.

• Experience with cloud services (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes).

• Knowledge of big data processing (Hadoop, Spark, or Apache Airflow) for handling astronomical datasets.

• Familiarity with astronomical data formats (FITS, HDF5) and scientific computing tools.

• Passion for space exploration, astronomy, or satellite technology.

Preferred Qualifications:

• Experience working with astronomical observatories, space agencies, or research institutes.

• Understanding of radio astronomy, optical telescopes, or space mission software.

• Contributions to open-source projects related to space science or DevOps.

Benefits:

• Work on cutting-edge space and astronomy projects.

• Collaborate with leading scientists and space agencies.

• Competitive salary and flexible work environment.

• Opportunity to contribute to groundbreaking astronomical discoveries.

Key Responsibilities:

• Design, implement, and validate security measures within .NET applications.

• Perform code reviews and vulnerability assessments.

• Collaborate with development teams to integrate security into the software lifecycle.

• Develop and enforce secure coding guidelines.

• Educate developers about secure coding standards and threat awareness.

• Stay current with security threats, trends, and technologies.

An Application Security Engineer (.NET) ensures that .NET-based applications are safeguarded against security risks by implementing proactive security strategies. This role involves code review, risk assessment, and close collaboration with developers to embed security practices into each phase of development. Acting as an expert resource, they provide guidance on secure coding and emerging threats, working to protect software assets and organizational data.

Overview:

A Data Ethicist focuses on ensuring that data-driven systems, especially those involving machine learning and AI, are designed, implemented, and maintained in ways that are ethical, fair, and transparent. This role sits at the intersection of data science, philosophy, policy, and law.

Key Responsibilities:

• Analyze datasets and algorithms for bias, fairness, and representativeness.

• Design ethical frameworks for AI and data usage.

• Work with data scientists, engineers, and product teams to implement responsible AI practices.

• Develop tools and metrics to audit models for ethical risk (e.g., fairness, privacy, transparency).

• Collaborate with legal and compliance teams to ensure adherence to regulations like GDPR, CCPA, or AI-specific laws.

• Educate stakeholders on data ethics principles.

Required Skills:

• Strong foundation in data science and machine learning.

• Understanding of ethical theory, philosophy, or AI ethics.

• Experience with explainable AI (XAI) tools and fairness libraries (e.g., IBM AIF360, SHAP, LIME).

• Ability to communicate complex ideas to non-technical stakeholders.

• Familiarity with privacy-enhancing technologies (e.g., differential privacy, federated learning).

About the Role

We are seeking a Cyber Security with strong expertise in implementing secure and compliant AI/ML solutions. The role will focus on ensuring responsible AI adoption, data security, compliance, and governance across AI/ML projects. The ideal candidate will have hands-on experience in security architecture, cloud platforms (especially Microsoft Azure), and governance frameworks, with proven knowledge of AI/ML lifecycle risks.

Key Responsibilities

• AI/ML Security & Governance

  • Design, implement, and manage governance frameworks for AI/ML systems to ensure compliance with regulatory, ethical, and organizational standards.

  • Assess AI/ML models and pipelines for risks such as bias, fairness, privacy, and explainability.

  • Define and enforce AI/ML security policies, controls, and monitoring mechanisms.

• Security Architecture (Azure Focused)

  • Design and maintain secure cloud-based ML/AI solutions on Microsoft Azure.

  • Implement Identity & Access Management (IAM), Key Vault, encryption, and security monitoring for ML workloads.

  • Support compliance with industry standards (ISO, GDPR, HIPAA, SOC2, etc.).

• Governance & Risk Management

  • Establish model governance, monitoring, and audit mechanisms across the ML lifecycle.

  • Conduct risk assessments and threat modeling for AI/ML applications.

  • Collaborate with compliance, risk, and IT security teams to ensure responsible AI adoption.

• Operational Excellence

  • Support incident response and vulnerability management for AI/ML environments.

  • Provide security awareness and governance best practices for AI/ML teams.

  • Document governance frameworks, security policies, and compliance reports.

Required Skills & Qualifications

• Experience:

  • 2.5+ years of professional experience in AI/ML governance, security, or cloud security architecture.

  • Hands-on experience with AI/ML model lifecycle security (data handling, training, deployment, monitoring).

• Technical Skills:

  • Strong knowledge of Microsoft Azure AI/ML services (Azure ML, Cognitive Services, Synapse).

  • Expertise in Azure Security architecture (Defender, Sentinel, Key Vault, IAM).

  • Understanding of data security, encryption, and compliance frameworks.

  • Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn) and MLOps concepts.

  • Knowledge of Responsible AI principles (bias detection, model explainability, privacy-preserving ML).

• Certifications (Required/Preferred):

  • Microsoft Certified: Azure Security Architect Expert (Required).

  • AI/ML Certification (e.g., Microsoft Certified: Azure AI Engineer Associate, AWS Machine Learning Specialty, or equivalent).

• Soft Skills:

  • Strong analytical and problem-solving skills.

  • Excellent communication and stakeholder management skills.

  • Ability to work cross-functionally with security, compliance, and data science teams.

Job Description:

We are looking for a Site Reliability Engineer with a passion for astronomy and space technology to join our team. In this role, you will work closely with astronomers, astrophysicists, and data scientists to develop, deploy, and manage scalable infrastructure for astronomical data processing, observatory automation, and space research applications.

Key Responsibilities:

• Design, implement, and maintain CI/CD pipelines for astronomical software and data processing workflows.

• Manage and optimize cloud-based infrastructure (AWS, Azure, or Google Cloud) for large-scale space data storage and analysis.

• Automate deployment, scaling, and monitoring of telescope control systems, astrophysics simulations, and satellite operations.

• Collaborate with scientists and engineers to integrate DevOps best practices into astronomical research projects.

• Implement containerization and orchestration (Docker, Kubernetes) for astronomical data pipelines.

• Enhance system reliability, security, and performance for astronomical observatories and space missions.

• Develop and maintain infrastructure as code (Terraform, Ansible, or CloudFormation).

• Monitor and troubleshoot system performance and astronomical data processing jobs.

Requirements:

• Bachelor's or Master’s degree in Computer Science, Astronomy, Astrophysics, or related fields.

• 3+ years of experience in DevOps, SRE, or Cloud Engineering.

• Proficiency in Linux, Shell scripting, Python, or Golang.

• Experience with cloud services (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes).

• Knowledge of big data processing (Hadoop, Spark, or Apache Airflow) for handling astronomical datasets.

• Familiarity with astronomical data formats (FITS, HDF5) and scientific computing tools.

• Passion for space exploration, astronomy, or satellite technology.

Preferred Qualifications:

• Experience working with astronomical observatories, space agencies, or research institutes.

• Understanding of radio astronomy, optical telescopes, or space mission software.

• Contributions to open-source projects related to space science or DevOps.

Benefits:

• Work on cutting-edge space and astronomy projects.

• Collaborate with leading scientists and space agencies.

• Competitive salary and flexible work environment.

• Opportunity to contribute to groundbreaking astronomical discoveries.