Abrar Admin

Optics11

<div>We are expanding our Underwater Acoustics R&amp;D team with a Signal Processing Engineer who is motivated to solve challenging scientific and engineering problems at the intersection of signal processing, applied mathematics, physics, and software engineering.
Optics11 is a deep-tech company developing advanced fiber-optic sensing technologies for demanding applications in underwater acoustics, offshore energy, and defense. Our novel fiber-optic technology is redefining underwater security by enabling next-generation sonar solutions to protect critical naval assets and underwater infrastructure.
You will contribute to the development of advanced sonar processing algorithms, mathematical models, and software for our next-generation fiber-optic sensing systems. Working closely with experts from multiple disciplines, you will help develop technologies that operate in some of the world's most challenging environments.
Previous experience in underwater acoustics, sonar, radar, geophysics or medical imaging is an advantage, but not a dealbreaker. We value strong analytical thinking, curiosity, and the willingness to learn new domains.<h4 class="jobSectionHeader">
Key responsibilities:</h4><ul><li>
Execute acoustic modelling and signal processing tasks: Implement and improve algorithms and mathematical models for underwater acoustic sensing systems using principles from signal processing, applied mathematics, statistics, physics, and numerical methods.</li><li>
Analyze and interpret experimental data: Process and evaluate fiber-optic datasets from laboratory and field trials to extract insights that support design improvements and validation.</li><li>
Develop and test algorithms: Contribute to the development and testing of algorithms for beamforming, event detection, filtering, and data classification under guidance from senior engineers.</li><li>
Document and communicate progress: Maintain clear, structured documentation of methods, results, and conclusions. Proactively communicate progress, challenges, and proposed solutions to the team.</li><li>
Collaborate across functions: Work closely with software, embedded, and hardware engineers to ensure smooth data flow, model integration, and system testing.</li><li>
Improve team workflows and tools: Identify opportunities to improve data handling, simulation scripts, and processing pipelines, contributing to better team efficiency and clarity.</li><li>
Share knowledge and provide feedback: Contribute to internal discussions by sharing your learnings, simplifying complex findings for others, and offering constructive feedback on shared work.</li></ul><h4 class="jobSectionHeader">
Why Join Us?</h4><ul><li>
Join one of Europe&rsquo;s most promising deep-tech scale-ups.</li><li>
Shape the future of a rapidly growing multidisciplinary R&amp;D organization.</li><li>
Competitive salary and benefits package.</li><li>
Enjoy regular team activities and company events.</li><li>
Fresh team lunches provided3 times/ week.</li></ul><h4 class="jobSectionHeader"> 
Required Qualifications:</h4><ul><li>
MSc degree (or equivalent) in Electrical Engineering, Applied Mathematics, Physics, Computer Science, Signal Processing, Statistics, Aerospace Engineering, Mechanical Engineering, or another quantitative discipline.</li><li>
1-3 years of experience in research or development, preferably with sensing systems, applied statistics, or wave-related phenomena or a PhD in a relevant discipline.</li><li>
A strong background in physical modelling, underwater acoustics, wave propagation, signal processing, sonar, applied mathematics, or equivalent.</li><li>
Good understanding of several of the following topics: digital signal processing, statistical signal processing, estimation theory, numerical methods, scientific computing Excellent programming skills (e.g. Python, Julia, C++, etc.) with readiness to deepen your programming proficiency.</li><li>
Strong analytical and problem-solving skills.</li><li>
You have a can-do mentality with no fear of getting your hands dirty when needed.</li><li>
You have strong verbal and written communication skills in English.</li><li>
You can work independently as well as in a team with well-developed communication skills.</li><li>
Knowledge of AI, machine learning techniques is a plus.</li><li>
Experience with CUDA, PyTorch, TensorFlow skills is a plus.</li><li>
Experience with fiber optic measurement principles and/or interferometry is a plus.</li><li>
Applicants should be eligible for NATO/Dutch security clearance.</li></ul>
Security &amp; Compliance:
You'll be working with clients in the defense and security sectors, obtaining a Certificate of No Objection issued by the AIVD (Dutch General Intelligence and Security Service) is mandatory. This means you will need to undergo a security screening. For more information, please refer to details on security screening.</div>

Signal Processing Engineer

<div>We are expanding our Underwater Acoustics R&amp;D team with a Hydrodynamic Acoustic Signature Engineer who is motivated to contribute to our acoustic intelligence capabilities by developing hydrodynamic, acoustic, and mechanical noise models.
Optics11 is a deep-tech company developing advanced fiber-optic sensing technologies for demanding applications in underwater acoustics, offshore energy, and defense. Our novel fiber-optic technology is redefining underwater security by enabling next-generation sonar solutions to protect critical naval assets and underwater infrastructure.
You will bridge first-principles physics and data-driven methods to support the development of classification and identification pipelines by linking acoustic signatures to identifiable target characteristics. Your expertise will contribute to threat spectrum definition and realistic operational scenarios. This is expected to be achieved by the development and maintenance of a deep physics-based understanding and models of underwater acoustic signatures. Working closely with experts from multiple disciplines, you will help develop technologies that operate in some of the world's most challenging environments.<h4 class="jobSectionHeader">
Key Responsibilities:</h4>
Hydrodynamics, Underwater Acoustic Emission and Signature Modelling:<ul><li>
Model hydrodynamic and mechanical noise generation mechanism of targets of interests, e.g., flow noise, cavitation, coupled structural vibration, that result in underwater acoustic noise.</li><li>
Translate physical phenomena into acoustic emission models, i.e., passive and target strength, to be used for system performance modelling.</li><li>
Define parametrized models capturing variability across operating conditions (speed, sea state, depth, configuration).Parameter Space &amp; Uncertainty Definition:</li><li>
Establish realistic parameter brackets for target surface/underwater kinematic parameters, e.g., speed, acceleration, maneuverability, etc., and for their related underwater acoustic signatures. This is based on physical principles and validated through experimental data.</li><li>
Quantify uncertainties and sensitivities to support robust system-level predictions.Data Processing &amp; Machine Learning:</li><li>
Generate synthetic data or semi-synthetic datasets based on physics-informed models.</li><li>
Define meaningful features derived from first principles and the properties of generation of underwater acoustic signatures.</li><li>
Support the development of classification models ensuring that models leveraging physics-based principles, for example making use of hand-crafted features.</li><li>
Support the development of pure data-driven ML/AI models by ensuring that models learn physically plausible patterns.</li><li>
Derive physics-based explanations from data-driven ML/AI models to support stakeholders&rsquo; decisions.</li><li>
Support other data processing pipelines, such as tracking (e.g., providing credible kinematic brackets) and detection (e.g., providing physically grounded inputs for detectability analysis, including array shape effects, effective aperture, and flow-induced performance degradation).</li></ul><h4 class="jobSectionHeader">
Why Join Us?</h4><ul><li>
Join one of Europe&rsquo;s most promising deep-tech scale-ups.</li><li>
Shape the future of a rapidly growing multidisciplinary R&amp;D organization.</li><li>
Competitive salary and benefits package.</li><li>
Enjoy regular team activities and company events.</li><li>
Fresh team lunches provided3 times/ week.</li></ul><h4 class="jobSectionHeader"> 
Required Qualifications:</h4><ul><li>
MSc degree (or equivalent) with 1-3 years&rsquo; industry experience in applied physics, hydrodynamics, mechanical engineering or a related field.</li><li>
A strong background in hydrodynamic modeling, acoustic modeling, physics-informed modeling, applied physics or equivalent.</li><li>
Strong programming skills (e.g. Python, Julia, C++, etc.) with readiness to deepen your programming proficiency.</li><li>
Strong analytical and problem-solving skills.</li><li>
You have a can-do mentality with no fear of getting your hands dirty when needed.</li><li>
You have strong verbal and written communication skills in English.</li><li>
You can work independently as well as in a team with well-developed communication skills.</li><li>
Experience with fiber optic measurement principles and/or interferometry is a plus.</li><li>
Applicants should be eligible for NATO/Dutch security clearance.</li></ul>
Security &amp; Compliance
You'll be working with clients in the defense and security sectors, obtaining a Certificate of No Objection issued by the AIVD (Dutch General Intelligence and Security Service) is mandatory. This means you will need to undergo a security screening. For more information, please refer to details on security screening.</div>

Hydrodynamic Acoustic Signature Engineer

<div>We are expanding our team with a Data &amp; ML Infrastructure Engineer who will take ownership of the platform that enables data ingestion, processing, storage, and machine learning workflows across multiple products. Operating at the intersection of data science, software engineering, and cloud infrastructure, you will build the foundations and ensure that our ML systems are scalable, reproducible, and production ready.
In this role, you will design, implement, and continuously improve a cloud-agnostic data and ML platform that supports multiple products and teams. You will be responsible for platform reliability, scalability, and cost-efficiency, while providing data scientists and ML engineers with the tools and infrastructure to efficiently develop, train, validate, and deploy machine learning models. You will serve as a technical bridge between the data science and IT/infrastructure teams, translating requirements into robust and maintainable systems.
This role includes ownership of an existing vendor-delivered platform and its evolution into a fully automated, reproducible, and multi-product ML platform.<h4 class="jobSectionHeader">
Key Responsibilities:</h4><ul><li>
Design, implement, and maintain the data and ML platform infrastructure, including systems for data ingestion, storage, processing, and training.</li><li>
Ensure high availability, reliability, and uptime of the platform, as it is critical to the business value proposition.</li><li>
Maintain and evolve vendor-delivered platform components and ensure long-term maintainability and independence.</li><li>
Build and maintain data workflows, including tools for dataset versioning, experiment tracking, and model lifecycle management across multiple products.</li><li>
Enforce DevOps / MLOps practices, including CI/CD pipelines, Infrastructure-as-Code, and automated workflows.</li><li>
Develop cloud-agnostic and containerized solutions that can run across public and private cloud environments within EU constraints.</li><li>
Optimize data storage, lifecycle policies, and cost efficiency, including tiered storage and retention strategies.</li><li>
Implement and maintain monitoring and alerting systems (e.g., Prometheus, Grafana) for pipelines, infrastructure, and resource usage.</li><li>
Ensure data governance, security, and compliance, including access control, audit logging, and anonymization requirements.</li><li>
Collaborate closely with data scientists, ML engineers, and IT teams to deliver infrastructure that meets operational needs.</li><li>
Manage resource and cost controls, including budgets, approvals, and tracking.</li><li>
Contribute to documentation, operational runbooks, and onboarding materials for the platform.</li></ul><h4 class="jobSectionHeader">
Why Join Us?</h4><ul><li>
Join one of Europe&rsquo;s most promising deep-tech scale-ups.</li><li>
Shape the future of a rapidly growing multidisciplinary R&amp;D organization.</li><li>
Competitive salary and benefits package.</li><li>
Enjoy regular team activities and company events.</li><li>
Fresh team lunches provided3 times/ week.</li></ul><h4 class="jobSectionHeader"> 
Required Qualifications:</h4><ul><li>
MSc or equivalent with 5+ years&rsquo; industry experience in Computer Science, Data Engineering, Machine Learning, or a related field.</li><li>
Strong experience with data platforms, cloud infrastructure, and distributed systems (AWS, GCP, Azure).</li><li>
Proven experience with Infrastructure-as-Code (e.g., Terraform) and automated deployments.</li><li>
Experience with ML platforms and tools (MLflow, Feast, DVC, DataHub or equivalent).</li><li>
Experience with AWS Sagemaker or Google Vertex AI platforms.</li><li>
Experience with databases (MongoDB, PostgreSQL, InfluxDB or equivalent).</li><li>
Experience with message brokers and streaming systems (Kafka, RabbitMQ or equivalent).</li><li>
Hands-on experience with containerization (Docker/OCI) and orchestration (Kubernetes or similar).</li><li>
Experience with CI/CD systems (e.g., GitLab CI).</li><li>
Programming skills in Python.</li><li>
Experience with monitoring and observability tools (Prometheus, Grafana).</li><li>
Understanding of DevOps and MLOps practices.</li><li>
Ability to work across teams and translate requirements into scalable infrastructure solutions.</li></ul>
Nice to Have:<ul><li>
Knowledge of data governance, IAM, and security frameworks.</li><li>
Experience with cost optimization and resource management in cloud environments.</li><li>
Familiarity with multi-tenant or multi-product platform architectures.</li><li>
Experience working with EU data compliance constraints in energy, maritime or defense.</li></ul>
Security &amp; Compliance:
You'll be working with clients in the defense and security sectors, obtaining a Certificate of No Objection issued by the AIVD (Dutch General Intelligence and Security Service) is mandatory. This means you will need to undergo a security screening. For more information, please refer to details on security screening.</div>

Data & ML Infrastructure Engineer

<div>
 We are expanding our team with a
 
 Data &amp; ML Infrastructure Engineer
 
 who will take ownership of the platform that enables data ingestion, processing, storage, and machine learning workflows across multiple products. Operating at the intersection of data science, software engineering, and cloud infrastructure, you will build the foundations and ensure that our ML systems are scalable, reproducible, and production ready.
 
 
 In this role, you will design, implement, and continuously improve a cloud-agnostic data and ML platform that supports multiple products and teams. You will be responsible for platform reliability, scalability, and cost-efficiency, while providing data scientists and ML engineers with the tools and infrastructure to efficiently develop, train, validate, and deploy machine learning models. You will serve as a technical bridge between the data science and IT/infrastructure teams, translating requirements into robust and maintainable systems.
 
 
 This role includes ownership of an existing vendor-delivered platform and its evolution into a fully automated, reproducible, and multi-product ML platform.
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Design, implement, and maintain the data and ML platform infrastructure, including systems for data ingestion, storage, processing, and training.
 </li>
 <li>
 Ensure high availability, reliability, and uptime of the platform, as it is critical to the business value proposition.
 </li>
 <li>
 Maintain and evolve vendor-delivered platform components and ensure long-term maintainability and independence.
 </li>
 <li>
 Build and maintain data workflows, including tools for dataset versioning, experiment tracking, and model lifecycle management across multiple products.
 </li>
 <li>
 Enforce DevOps / MLOps practices, including CI/CD pipelines, Infrastructure-as-Code, and automated workflows.
 </li>
 <li>
 Develop cloud-agnostic and containerized solutions that can run across public and private cloud environments within EU constraints.
 </li>
 <li>
 Optimize data storage, lifecycle policies, and cost efficiency, including tiered storage and retention strategies.
 </li>
 <li>
 Implement and maintain monitoring and alerting systems (e.g., Prometheus, Grafana) for pipelines, infrastructure, and resource usage.
 </li>
 <li>
 Ensure data governance, security, and compliance, including access control, audit logging, and anonymization requirements.
 </li>
 <li>
 Collaborate closely with data scientists, ML engineers, and IT teams to deliver infrastructure that meets operational needs.
 </li>
 <li>
 Manage resource and cost controls, including budgets, approvals, and tracking.
 </li>
 <li>
 Contribute to documentation, operational runbooks, and onboarding materials for the platform.
 
 
 
 </li>
 </ul>
 
 Why Join Us?
 
 
 
 <ul>
 <li>
 Join one of Europe&rsquo;s most promising deep-tech scale-ups.
 </li>
 <li>
 Shape the future of a rapidly growing multidisciplinary R&amp;D organization.
 </li>
 <li>
 Competitive salary and benefits package.
 </li>
 <li>
 Enjoy regular team activities and company events.
 </li>
 <li>
 Fresh team lunches provided3 times/ week.
 
 
 
 </li>
 </ul>
 Required Qualifications:
 
 
 <ul>
 <li>
 MSc or equivalent with 5+ years&rsquo; industry experience in Computer Science, Data Engineering, Machine Learning, or a related field.
 </li>
 <li>
 Strong experience with data platforms, cloud infrastructure, and distributed systems (AWS, GCP, Azure).
 </li>
 <li>
 Proven experience with Infrastructure-as-Code (e.g., Terraform) and automated deployments.
 </li>
 <li>
 Experience with ML platforms and tools (MLflow, Feast, DVC, DataHub or equivalent).
 </li>
 <li>
 Experience with AWS Sagemaker or Google Vertex AI platforms.
 </li>
 <li>
 Experience with databases (MongoDB, PostgreSQL, InfluxDB or equivalent).
 </li>
 <li>
 Experience with message brokers and streaming systems (Kafka, RabbitMQ or equivalent).
 </li>
 <li>
 Hands-on experience with containerization (Docker/OCI) and orchestration (Kubernetes or similar).
 </li>
 <li>
 Experience with CI/CD systems (e.g., GitLab CI).
 </li>
 <li>
 Programming skills in Python.
 </li>
 <li>
 Experience with monitoring and observability tools (Prometheus, Grafana).
 </li>
 <li>
 Understanding of DevOps and MLOps practices.
 </li>
 <li>
 Ability to work across teams and translate requirements into scalable infrastructure solutions.
 
 
 
 </li>
 </ul>
 
 Nice to Have:
 
 
 
 <ul>
 <li>
 Knowledge of data governance, IAM, and security frameworks.
 </li>
 <li>
 Experience with cost optimization and resource management in cloud environments.
 </li>
 <li>
 Familiarity with multi-tenant or multi-product platform architectures.
 </li>
 <li>
 Experience working with EU data compliance constraints in energy, maritime or defense.
 
 
 
 </li>
 </ul>
 
 Security &amp; Compliance:
 
 
 
 You'll be working with clients in the defense and security sectors, obtaining a Certificate of No Objection issued by the AIVD (Dutch General Intelligence and Security Service) is mandatory. This means you will need to undergo a security screening. For more information, please refer to details on security screening.
</div>

Join Optics11 and explore 4   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Optics11

About Company

Signal Processing Engineer

Hydrodynamic Acoustic Signature Engineer

Data & ML Infrastructure Engineer

Data & ML Infrastructure Engineer