Deep Learning Engineer Intern Job at Implicity (Paris)

Machine Learning Engineering Intern

At Cresta, the Knowledge Assist (KA) team develops AI solutions for the contact ...

Location

Canada , Toronto

Salary:

45.00 - 70.00 USD / Hour

Cresta

Expiration Date

Until further notice

Requirements

Currently pursuing a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field
Proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow)
Strong understanding of machine learning fundamentals and generative modeling
Ability to design and analyze experiments involving large-scale datasets
Work authorization in the country of employment at the time of hire

Job Responsibility

Design, develop, and deploy Cresta’s KA solutions and proprietary models
Focus on practical AI challenges such as improving reasoning, and evaluation in real-world scenarios
Collaborate with cross-functional teams including front-end and back-end software engineers to integrate KA solutions into Cresta’s customer solutions
Lead initiatives to scale AI systems for production environments, ensuring performance and reliability across use cases
Contribute to solving cutting-edge problems in AI and help define the future roadmap for Cresta’s KA
Innovate and research ways to improve security, cost-efficiency, and reliability of AI systems

What we offer

Lunch can be expensed (up to $25) while working in the office
PTO: 4 days
Compensation for this position includes a base salary, equity, and a variety of benefits

Senior machine learning engineer

Location

Japan , Tokyo

Salary:

10000000.00 - 16000000.00 JPY / Year

Randstad

Expiration Date

October 11, 2027

Requirements

Empathy with mission, vision and values
6+ years' experience working as a software/machine learning engineer
5+ years' experience as a Machine Learning Engineer
4+ years' experience as a Deep Learning engineer
Experience in developing GNN or generative models or Geometric Deep Learning
At least 2 publications as first author in international conferences/ journals

Job Responsibility

Appropriate design of evaluation methods based on task-specific understanding of metric properties
Hypothesis proposal, development implementation and performance validation of machine learning models for compound information
Proposal and creation of features according to data and purpose
MLOps, implementation of distributed computing environments
Training machine learning models, exploring and adding data to be used for inference
Search for relevant papers, application and validation of concepts

What we offer

休憩室
更衣室
健康保険
厚生年金保険
雇用保険
賞与

Fulltime

Artificial intelligence-assisted Reliability Engineer Intern

Amazon development center develops innovative consumer-centric safety total solu...

Location

Taiwan , Taipei

Salary:

Not provided

Amazon Pforzheim GmbH

Expiration Date

Until further notice

Requirements

Enrolled in or have completed a Master's degree or above in engineering or equivalent
Speak, write, and read fluently in Mandarin
Currently enrolled in a master’s program in Computer Science, Electrical Engineering, Chemical Engineering, Mechanical Engineering, or related field with focus on deep learning and computer vision
Programming experience in C++ and Python
Experience in implementing computer vision algorithms using multiple toolkits
Proficient in both English and Chinese

Job Responsibility

Develop and implement novel machine learning algorithms, focusing on computer vision and generative AI applications
Design and optimize scalable AI systems for large-scale datasets, ensuring high performance and accuracy
Apply state-of-the-art Machine Learning and AI research to solve complex reliability challenges and product lifespan projection
Create clear technical documentation and reports to effectively communicate concepts and results
Work closely with senior reliability engineers in reporting reliability execution progress, and failure analysis
Participate in evaluating and developing reliability test methodologies to reduce test time and increase test coverage

Parttime

Machine Learning Engineer

We are seeking a talented and experienced Machine Learning Engineer with experti...

Location

United States , Boston

Salary:

Not provided

Robert Half

Expiration Date

Until further notice

Requirements

3+ years of professional experience working as a Machine Learning Engineer or in a related role focused on computer vision
Strong proficiency in Python and experience with deep learning libraries such as TensorFlow, PyTorch, or Keras
Hands-on expertise with computer vision models and architectures, including YOLO, U-Net, and CNNs/RCNNs
Extensive experience with image segmentation, object detection, and related computer vision techniques
Familiarity with preprocessing methods like image blurring and contrast enhancements to improve model outcomes
Proven ability to build and deploy production-ready code for machine learning models at scale
Understanding of best practices for scalable system design, deployment, and maintenance of machine learning pipelines
Strong problem-solving skills and a passion for tackling complex, unstructured problems in the domain of computer vision
Effective verbal and written communication skills to articulate solutions to both technical and non-technical stakeholders.

Job Responsibility

Design, develop, and deploy scalable and production-ready computer vision models for real-world applications
Leverage algorithms and frameworks like YOLO, U-Net, CNNs/RCNNs, and other deep learning architectures for tasks such as image segmentation, object detection, and classification
Implement pre- and post-processing techniques, including image blurring, contrast enhancements, and other image augmentation pipelines, to optimize model performance
Write efficient, maintainable, and clean Python code for integrating computer vision models into production systems
Collaborate with cross-functional teams, including data scientists, machine learning engineers, and product managers, to understand project needs and deliver solutions
Analyze and improve model performance, accuracy, and efficiency through continuous evaluation and enhancement
Stay updated on the latest advancements in computer vision and machine learning techniques, incorporating new technologies where appropriate
Contribute to model optimization and inference processes to ensure scalability and low latency in production environments
Troubleshoot production issues and implement solutions to improve reliability and performance
Document technical solutions, workflows, and methodologies for internal and external stakeholders.

What we offer

Access to top jobs
Competitive compensation
Medical insurance
Vision insurance
Dental insurance
Life and disability insurance
Company 401(k) plan
Free online training.

Fulltime

Distinguished Technologist, Deep Learning

Joining our HPE Hybrid Cloud team and working as part of our OpsRamp team is a c...

Location

United States , San Jose

Salary:

164500.00 - 398500.00 USD / Year

Hewlett Packard Enterprise

Expiration Date

Until further notice

Requirements

15+ years of relevant experience in the industry delivering technical and business strategy at an advanced/strategist level
Master's, or PhD degree in Computer Science, Information Systems, Engineering, or equivalent
At least 4 years of hands-on expertise in defining, building, training and / or optimizing foundational deep learning models at scale in PyTorch, HF and other ML frameworks and libraries
Experience and/or deep understanding in various deep learning architectures like CNNs, GNNs, Transformers, Reinforcement Learning etc. is a strong advantage
Strong hands-on experience/understanding in pre-training, fine-tuning, distilling, aligning open-source large language models and have them complement the in-house foundational models
Hands-on experience developing multi-agent applications around a mixture of in-house and open-source models while leveraging latest in RAG and Prompt Engineering tooling techniques
Strong customer focus and obsession with improving service availability/performance and user experience/consumption using measurable SRE metrics
Must have a track record of working alongside other engineering teams architecting, building, and deploying mission-critical, highly distributed, large-scale SaaS applications
Must have strong knowledge of application failure modes, resiliency patterns, and techniques to enable robust, self-healing architecture
Effective technical leadership skills to influence diverse groups to move toward common goals/strategies

Job Responsibility

Oversee build of OpsRamp’s CoPilot for Autonomous Operations for the Hybrid Cloud
Understand latest in GenAI/ML for ITOM
Understand cloud-native architecture concepts and have knowledge of best practices for high availability, scalability, resilience, performance, and security requirements in the cloud
Act as a cross-functional product and technical expert for GenAI within engineering with close working relationships with customers, product management, support, and marketing supporting edge-to-cloud services offering
Provides consultation, design input, and feedback for product development and design reviews across multiple organizations and architectures
Help transition proof-of-concept implementations into R&D teams to accelerate new product delivery
Creates technical content such as designs, specifications, and initial software implementations
Guides and mentors less-experienced staff members to set an example of software systems design and development innovation and excellence, helping to grow engineers into more senior technical roles
Collect product feedback from field interactions to provide input into Engineering and Product Management to influence product roadmap direction
Maintain a high level of knowledge of OpsRamp SaaS product and product road maps, as well as that of the competition and prospective strategic partners

What we offer

Health & Wellbeing
Personal & Professional Development
Unconditional Inclusion

Fulltime

Reinforcement learning intern

As a Reinforcement Learning Intern, you will help develop and implement learning...

Location

France , Paris

Salary:

Not provided

Enchanted Tools

Expiration Date

Until further notice

Requirements

BSc holder in Robotics, Engineering, Computer Science, or related field
Coursework or project experience in reinforcement learning or learning-based control
Strong Python skills and knowledge of a deep learning framework PyTorch, JAX, or TensorFlow
Familiarity with simulation environments such as Isaac Sim, Mujoco, or Gazebo
Solid analytical and problem-solving abilities

Job Responsibility

Develop, debug, and test reinforcement learning algorithms for locomotion and navigation on a dynamically balancing base
Extend simulation environments (Isaac Sim / Isaac Lab) to support training and evaluation of RL policies
Integrate trained policies into the Mirokai software stack and validate them on physical robots
Analyze performance, stability, and sim-to-real transfer aspects
Stay up to date with recent research in reinforcement learning for robotics

AI Research Engineer - Reinforcement Learning

At Helsing we deliver AI-based capabilities and the enabling infrastructure that...

Location

Germany , Munich

Salary:

Not provided

Helsing

Expiration Date

Until further notice

Requirements

Hold MSc in machine learning with a speciality in either reinforcement learning, multi-agent systems, automation and control, or robotics
Have excellent communication skills and the ability to report and present research findings clearly and efficiently both internally and externally
Are passionate about keeping up-to-date with current research and enjoy reimplementing / extending papers on state-of-the-art Deep Learning-based approaches
Possess solid software engineering skills, writing clean and well-structured code in Python and/or languages like Rust, Java, or modern C++, and experience deploying AI software to production including testing, QA, and monitoring

Job Responsibility

Design, train and deploy agents in complex multi-agent environments
Contribute to our reinforcement learning stack by implementing, improving and extending the current state of the art in multi-agent reinforcement learning
Be a part of impactful projects and will collaborate with people across several teams and backgrounds to integrate cutting edge ML/AI in our production systems

What we offer

Competitive compensation and stock options
Relocation support
Social and education allowances
Regular company events and all-hands to bring together employees as one team across Europe
A hands-on onboarding program (affectionately labelled “AI-duction”), in which you will be familiarising yourself with our tools and ML pipelines used across the company

Fulltime

Algorithm Engineer IV

Beacon Biosignals is on a mission to revolutionize precision medicine for the br...

Location

United States , Boston

Salary:

Not provided

Beacon Biosignals

Expiration Date

Until further notice

Requirements

More than 5 years of industry experience in machine learning and deep learning, particularly in health sciences or other regulated fields, with a proven track record of bringing algorithms into production
Experienced with digital signal processing (DSP) and statistics
Proficient in using PyTorch (preferred) or other deep learning frameworks for training, developing, and deploying deep learning models
Proficient with latest Deep Learning advances (Transformer/ViT, large scale modeling, large model training, ...)
Follow and spread best practices in software and ML engineering, including testing, version control, code reviews, documentation, Dockerization, CI/CD, and experiment tracking
Experienced with biosignals, medical imaging data, or large time-series datasets, or are enthusiastic about learning more in the domain
Thrive in a team environment, recognizing that collaboration, open communication, and continuous feedback are essential for collective success
Can distill, discuss, and present complex technical topics in a way that is appropriate for the audience at hand, both internally and externally
Excited to participate in the entire algorithm development lifecycle, which spans scoping, data wrangling, algorithm development/experimentation, formal validation, quality/regulatory documentation, production deployment, and working with clients who might benefit from these algorithms

Job Responsibility

Participate in and lead the entire biosignal-based algorithm development lifecycle for medical devices including specifications and requirements gathering, data curation and labeling, development, failure-analysis, production, maintenance, and documentation
Select, implement, and develop the most appropriate method for each problem, knowing when to apply deep learning techniques and when other methods are more effective
Enhance our internal deep learning and machine learning tools to boost team efficiency, introduce new model architectures and algorithmic techniques, and refine the codebase to encourage reusability where needed to enable rapid experimentation
Spread and improve our best practices to ensure algorithm implementations are user-friendly, well-documented, and thoroughly tested, including unit tests, comprehensive documentation, CI, and non-regression testing
Present results to key stakeholders and assist them in utilizing algorithms for client engagement
Support the client-facing projects to understand and shape the impact Beacon algorithms have for our customers, both for existing deployed algorithms, and future algorithm development

What we offer

Equity
PTO

Deep Learning Engineer Intern

Implicity

Location:
France , Paris

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
March 22, 2026

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Job Description:

Job Responsibility:

Requirements:

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