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Senior Machine Learning Engineer
Location: Dublin,Ireland

Are you an ML Engineer excited by the idea of building large scale 
conversational AI systems? 
Or Building and evolving production ML infrastructure for the latest technologies in the AI sector today?

If yes then check out the below:

While not yet industry leading, my client is taking on the giants of today in Conversational and CX AI. 

How? by playing to their strengths; taking bigger risks, thinking more long-term and differentiating with AI. They have a clear vision for the future & are able to move at high speeds. 

Now scaling their Machine Learning Engineering team this person will be 
a key contributor in not only the building and scaling of the ML infrastructure but how they put complex ML , Deep Learning and NLP systems into production. 

What's in it for you? 
  • Base salary of up to €140k plus RSU's
  • Health and dental insurance
  • Breakfast and lunch provided every weekday
  • Open vacation policy and flexible holidays
  • Work at the edge of AI innovation like LLMs, NLP, Deep Learning
  • Relocation and Visa Support is also available

Sounds good? 

Check the below to see how to be successful in this role:

As a Senior ML Engineer you will be expected to have spent at least 5+ years:

  • Building and shipping ML systems into production
  • Managing large batches of ML experiments using tools like MLFlow
  • Expertly writing, testing, deploying, debugging and monitoring software in Python or similar
  • Contributing to the design and architecture of distributed systems
  • Building or contributing to the building of Data or ML infrastructures. 
If you think you could thrive in this role get in touch to discuss further via apply or drop me an email at anthonyh@alldus.com

Our client are utilizing machine learning and data science to revolutionize the marketing sector and they are hiring a Machine Learning Engineer to join their team. The successful candidate will have a crucial role in crafting and deploying models that deliver substantial value for the company's clientele.


Responsibilities

  • As the Machine Learning Engineer, you will create models to improve marketing strategies and boost customer engagement.

  • Establish a resilient and scalable machine learning infrastructure for deploying models in production settings.

  • Iterate regularly on models and algorithms to enhance their effectiveness and performance.



Skillset

  • Ph.D. or Master’s degree in a relevant field.

  • 5 years of software engineering experience focused on machine learning systems, platforms and/or applications.

  • Thorough understanding of contemporary machine learning approaches and algorithms.

  • Proficient in Python and related scientific libraries (e.g., numpy, pandas).

  • Hands-on experience with machine learning frameworks like PyTorch, Spark ML and scikit-learn.

  • Knowledge of machine learning infrastructures and scalable system design.

  • Proven ability to tackle problems comprehensively, from inception to resolution, with a proactive approach to learning new skills as required.



Benefits

  • Salary: $180,000 to $250,000

  • Healthcare

  • 401k

  • Flexible PTO



Interested? Apply now in the link below or email your resume to angelo@alldus.com for consideration.

Our client are a Series-A Software Company at the forefront of LLM innovation.  They are hiring a Machine Learning Research Engineer to join their team and be responsible for spearheading state-of-the-art research to develop and enhance our agentic system. The successful candidate will play a pivotal role in creating new experiment ideas, optimizing product performance and driving innovation through advanced machine learning techniques.


Responsibilities:

  • As the ML Research Engineer, you will lead state-of-the-art research to develop and improve the agentic system.

  • Generate new experiment ideas to optimize product performance and enhance user experience.

  • Spearhead dataset collection, generation and optimization efforts to support model training and evaluation.

  • Own key technical areas including model/inference optimization, distributed training, fine-tuning, instruction fine-tuning, and multi-modal LLMs.

  • Collaborate closely with cross-functional teams to translate research findings into actionable insights and product enhancements.

  • Stay updated with the latest advancements in machine learning and related fields, and actively contribute to the company's intellectual property through patents and publications.

 

Skillset:

  • PhD, Master’s or Bachelor's degree in Computer Science, Engineering, Mathematics or similar.

  • At least three years of industry experience in machine learning research and development.

  • Demonstrated expertise in machine learning techniques, particularly in transformer-based systems.

  • Proven track record of impactful contributions to machine learning research, with at least one first-author publication in a reputable conference or journal.

  • Strong programming skills in Python and proficiency with machine learning libraries (e.g., TensorFlow, PyTorch).

  • Experience with large-scale dataset management, distributed computing, and cloud platforms (e.g., AWS, GCP).

  • Excellent problem-solving abilities and analytical thinking.



Salary: circa. $200k


Interested? Apply now in the link below or email you resume to angelo@alldus.com for consideration.

Our client are a dynamic fintech startup revolutionizing their industry with innovative LLM-powered SaaS solutions. They are hiring a Director of Machine Learning to lead their machine learning initiatives and drive the development of high-performance enterprise solutions that leverage LLMs and RAG architectures.


Responsibilities:

  • As the Director of Machine Learning, you will lead the development and execution of the machine learning roadmap, aligning with business objectives and customer needs.

  • Build and mentor a high-performing machine learning team, fostering a culture of collaboration, innovation and continuous learning.

  • Drive the design, development and optimization of LLM-powered SaaS solutions, ensuring scalability, reliability and performance.

  • Collaborate closely with cross-functional teams, including product management, engineering and data science, to translate business requirements into technical solutions.

  • Stay abreast of the latest advancements in machine learning, NLP and related fields, and evaluate emerging technologies for potential integration into their platform.

  • Provide technical leadership and guidance, ensuring best practices, coding standards and quality assurance processes are followed.

  • Drive the adoption of fine-tuning and instruction fine-tuning techniques to optimize model performance and adaptability to specific domains.



Skillset:

  • PhD or Master's degree in Computer Science, Engineering, Mathematics, or a related quantitative discipline.

  • Minimum of eight years of experience in machine learning, with at least three years in a hands-on leadership role.

  • Proven track record of building and leading high-performing machine learning teams, delivering successful enterprise solutions from concept to production.

  • Extensive experience with LLMs, RAG architectures and other advanced machine learning techniques, with a focus on natural language processing.

  • Strong background in fine-tuning and instruction fine-tuning, with a deep understanding of model optimization techniques.

  • Experience working in the fintech industry or related domains is highly desirable.

  • Excellent communication and interpersonal skills, with the ability to effectively communicate complex technical concepts to non-technical stakeholders.

  • Strong problem-solving abilities and strategic thinking, with a passion for driving innovation and delivering impactful results.



Salary: TBC by our client


Interested? Apply now in the link below or email you resume directly to angelo@alldus.com for consideration.

Our client is a Series A startup within the Generative AI space and they are hiring an Engineering Manager to join the team. Backed by one of the leading venture capital firms in the industry, this is an exciting opportunity to join a SaaS company that is revolutionizing their industry.  This role is a mix of managerial (60%) and technical (40%) responsibilities.


Managerial Responsibilities

  • As the Engineering Manager, you will lead and mentor a team of engineers, and help foster a culture of innovation, collaboration and continuous improvement.

  • Develop and execute the technical strategy, as well as Establish and maintain best practices around engineering including methodologies and processes.

  • Oversee the entire software development lifecycle, from requirements gathering, design, implementation, testing and deployment.

  • Collaborate with cross functional teams to ensure the successful delivery of high-quality solutions.

  • Drive the use of new technologies and tools to enhance the teams capabilities.


Technical responsibilities

  • Lead full cycle software development.

  • Engage with product and design team to translate user requirements into technical implementations.

  • Participate in coding, code reviews and technical problem solving.

  • Enhance system performance, reliability and security.

  • Implement and optimize software components.



Skillset:

  • Degree in Computer Science, Engineering or related field.

  • Proven expertise in React/Next.JS.

  • Proficiency in PostgreSQL and Azure Cloud services.

  • Experience with Python.

  • Minimum of 5 years in web development or similar experience with a focus on SaaS platforms.

  • Deep expertise in software development, architecture and cloud technologies.

  • Strong leadership skills with the ability to build and mentor high performing teams.

  • Proficiency in agile methodologies.

  • US citizenship is a must with the ability to pass a Federal background check.



Benefits:

  • Salary: Circa $200k.

  • Stock options.

  • Comprehensive benefits package.

  • Remote working anywhere in the U.S.



Interested? Apply now in the link below or email your resume directly to matthew@alldus.com for consideration. 

Engineering Manager - Data Science & Machine Learning
Location: Berlin, Germany

Are you a Data Science or Machine Learning Manager tired of the lack of investment or buy in from your executives? 

Or searching for that excitement again when building products that you can directly see tangible outcomes? 

If yes, check out the below:

An industry leading org built around fairness and sustainability within adtech is building products that can handle 400 billion auctions per day. 

Exceeding that of any Google or Amazon programmatic ad marketplace.The ML team is building products that help increase latency and speed. 

A globally distributed team with the bulk of the Data Science & Machine Learning org in Berlin. Their Executives call the ML team the "secret sauce" to their evolution. 

What's in it for you? 
  • Salary €140-160k
  • Hybrid Working environment
  • Build at Scale - work on products that overshadow Google and Amazon search scales AND see direct impact through visible KPI's
  • Buy in from Execs - No headaches around trying to get the smallest thing approved.
  • Work in an environment that believes in constantly innovating with a product mindset (iterate , test then build)
  • Progression - room to grow into a senior and then director. 
Sounds good? 

Check the below to see how to be successful in this role

What will you need to be successful? 

As the Engineering Manager you will be the right hand of the VP of ML.
To succeed in this role you need the core 4 skills. 

1. People Leadership:
  • Get into the heads of your engineers understand their strengths and weaknesses, empower them , grow them understand how changes can benefit them.
  • You need to know how to make your team tick in sync and proven experience of doing this before. 
2. Processes: 
  • They are no longer a startup, moving from scrappy to self-sufficient & organized is a big goal for this Data Science team. Getting your team processes structured and self sufficient is a key piece of the puzzle for this hire to be successful. 
3. Data Science & ML: 
  • You need to know how these models work and all the different variables that can go wrong. Models outputs are not always 100% accurate. 
  • While not expecting you have Spidey like senses the data science intuition of knowing that a models output may be missing something is really critical and saves them a lot of €€€'s. 
4. Engineering:
  • While any ML org would love just to do R+D the team have to make money. So having successfully built and launched products in Machine learning is the final core skill for the Engineering Manager. 
  • Understand the challenges and how to of getting Data Science and ML models into production and the lifecycle of an ML product will help you achieve success in this role.

If you think you could thrive in this role get in touch via apply or drop me an email at anthonyh@alldus.com