Senior/Staff ML Architect

Senior/ Staff Machine Learning Architect

Who are we

Founded with the goal of helping organizations continuously improve their security posture, we have built our company on the foundation of penetration testing and vulnerability research, and our team of intelligence experts are some of the best in the industry.

Securin offers a comprehensive portfolio of Products, including Attack Surface Management (ASM), Vulnerability Intelligence (VI), Application Security posture management (ASPM) , Services like Penetration Testing, and Vulnerability Management.

These capabilities allow our customers to gain complete visibility of their attack surface, stay informed of the latest security threats and trends, and proactively address their risks. By utilizing these services together, clients can have a proactive and holistic view of their security posture and protect their assets from the most advanced and dynamic attacks.

Securin's Vision

We promise continuous security posture improvement, enhanced attack surface visibility, and proactive prioritization of remediation for every business.

What do we deliver

Companies do not need another tool; they need expertise and talent. Securin acts as an extension of your security team. We help identify and remediate the most dangerous exposures, vulnerabilities, and risks that exist in your environment and deliver predictive and definitive intelligence to facilitate proactive remediation. Our combination of domain expertise, cutting-edge technology, and services makes Securin a leader in the cybersecurity industry.

Description:

The Machine Learning Architect is responsible to scale the machine learning models across the entire organization. They are responsible for building and maintaining the infrastructure that will allow this scaling to occur. Identify best practices to implement ML solutions and build test cases to analyze the efficiency of the algorithms.

Responsibilities:

Architect and refine ML models and algorithms, translating complex datasets into actionable solutions.

Engage in the full lifecycle of data modeling projects, from understanding business requirements to deployment and monitoring.

Execute comprehensive data analysis, including preprocessing, feature engineering, and leveraging Generative AI algorithms for novel solutions.

Get the pipelines up and running, setting up CI/CD, firewalls, and tracking for the longevity of machine learning models.

Apply advanced analytical techniques to analyze vast datasets, identifying trends, anomalies, and opportunities for improvement.

Execute data preprocessing, feature engineering, and algorithm optimization to enhance model accuracy and efficiency.

Conduct exploratory data analysis to extract valuable insights and influence strategic decisions.

Keep abreast of and implement the latest ML trends, tools, and best practices, including AutoML, MLOps, and interpretability frameworks.

Stay ahead of AI research, especially in Generative AI, applying the latest findings and techniques to drive innovation within our projects.

Required Qualifications:

Degree in Computer Science, Engineering, Statistics, or a related technical field.

Minimum 5+ years of relevant experience in machine learning and deep learning frameworks

Proficiency of machine learning frameworks: TensorFlow, PyTorch, Keras, Scikit-Learn.

Demonstrable experience in machine learning, deep learning, NLP, computer vision, reinforcement learning, and/or other AI domains.

Experience with MLOps tools such as ModelDB, Cubeflow, Pachyderm, and Data Version Control (DVC).

Experience in supporting model builds and model deployment for IDE-based models and autoML tools, experiment tracking, model management, version tracking & model training (Dataiku, Datarobot, Cubeflow, MLflow, neptune.ai), model hyperparameter optimization, model evaluation, and explainability (SHAP, Tensorboard)

Strong foundational understanding of algorithmic complexity and data structure optimization.

Managing experience of more than 6 machine learning projects end-to-end, with the focus on MLOps.

Have a good grasp of CI/CD pipelines, IaC (Infrastructure-as-code) tools (like Terraform, CloudFormation),

Excellent problem-solving, collaboration, and communication abilities.

Excellent communication and problem-solving skills

Nice to Have Qualifications:

Background in cloud computing and big data platforms (AWS, Azure, GCP), with hands-on experience in cloud-based ML services and serverless architectures.

Knowledge and practical experience with MongoDB and Elasticsearch

Experience in distributed computing

Experience with SQL/NoSQL databases, data visualization tools, and version control systems.

Why should we connect

We are a bunch of passionate cybersecurity professionals who are building a culture of security. Today, cybersecurity is no more a luxury but a necessity with a global market value of $150 billion.

At Securin, we live by a people-first approach. We firmly believe that our employees should enjoy what they do. For our employees, we provide a hybrid work environment with competitive best-in-industry pay, while providing them with an environment to learn, thrive, and grow. Our hybrid working environment allows employees to work from the comfort of their homes or the office if they choose to. For the right candidate, this will feel like your second home.

If you are passionate about cybersecurity just as we are, we would love to connect and share ideas.