README.md

---
tags:
- spacy
- token-classification
- ner
- named entity recognition
- job description named entity recognition
widget:
- text: >-
    Responsibilities


    As a Director of Engineering - Backend, your day-to-day activities will
    revolve around technical leadership, effective communication, and a hands-on
    approach to solving complex challenges, contributing to the overall success
    of the backend team and the company.


    Technical Leadership


    Set the technical direction and architecture for the backend engineering
    team.

    Architect scalable and resilient solutions leveraging AWS services.

    Drive the adoption of best practices in coding standards, testing, and
    deployment processes.

    Hands on development, design, and execution as a player-coach with the
    backend engineering team.


    People Leadership


    Mentor and coach engineers at all levels, providing guidance on technical
    and career development.

    Foster a culture of collaboration, learning, and innovation within the team.

    Conduct regular 1:1s and yearly performance reviews and provide constructive
    feedback to support individual growth.


    Project Management


    Prioritize and allocate resources effectively to meet project deadlines and
    deliverables.

    Coordinate with Product, QA, and other cross-functional teams to gather
    requirements and ensure successful project execution.

    Monitor project progress, identify risks, and implement mitigation
    strategies as needed.

    Drive continuous improvement in project management processes and
    methodologies.


    System Architecture


    Design and implement scalable and reliable backend systems using
    technologies like Python, Java, Docker, and Elasticsearch.

    Utilize Terraform for infrastructure as code to automate provisioning and
    deployment tasks on AWS.

    Optimize database performance and reliability across PostgreSQL, MySQL, and
    DynamoDB.

    Implement and drive CI/CD, monitoring, and alerting solutions to ensure
    system health and performance.


    Team Collaboration


    Collaborate closely with frontend and other cross-functional teams to design
    and implement end-to-end solutions.

    Conduct code reviews and provide technical guidance to ensure code quality
    and consistency.

    Foster a culture of knowledge sharing and continuous learning through tech
    talks, brown bag sessions, and workshops.

    Encourage a collaborative and inclusive work environment where diverse
    perspectives are valued.


    Quality Assurance


    Implement automated testing strategies to ensure the reliability and
    stability of backend services.

    Establish and enforce coding standards, code reviews, and testing practices.

    Work closely with QA engineers to develop and maintain comprehensive test
    suites.

    Continuously monitor and improve the quality of code and systems through
    metrics and feedback loops.


    Strategic Planning


    Collaborate with senior leadership to align technical initiatives with
    business goals and objectives.

    Provide input into the product roadmap based on technical feasibility and
    resource constraints.

    Identify opportunities for innovation and optimization to drive business
    value and competitive advantage.


    Skills and Experience


    8+ years of experience in software engineering, with a focus on backend
    development as an IC/Staff or Architect level role.

    4+ years of experience in a leadership or management role, preferably in a
    technology-driven organization

    Proven track record of successfully leading and mentoring engineering teams

    Ability to prioritize and manage multiple projects and deadlines effectively

    Extensive experience with cloud technologies, particularly AWS, including
    designing and implementing scalable solutions

    Strong proficiency in at least one backend programming language such as
    Python or Java, with a deep understanding of its ecosystem and best
    practices

    Hands-on experience with infrastructure as code tools like Terraform for
    managing cloud resources

    Experience with containerization and orchestration using Docker and
    container orchestration services

    In-depth knowledge of database systems, including both relational (e.g.,
    PostgreSQL, MySQL) and NoSQL (e.g., DynamoDB) databases, and their
    optimization

    Demonstrated expertise in implementing and maintaining continuous
    integration and deployment pipelines, ideally using Github Actions

    Proficiency in version control systems like GitHub, including branching
    strategies and pull request workflows

    Familiarity with search technologies such as Elasticsearch and query
    optimization techniques

    Strong problem-solving skills and the ability to make sound technical
    decisions in a fast-paced environment

    Excellent communication and collaboration skills, with the ability to work
    effectively with people and across teams and departments

    Bachelors or Masters in Computer Science, Engineering or other related
    technical field


    Technologies we use


    Python

    Terraform

    AWS

    Java

    Docker

    Databases (PostgreSQL, MySQL and DynamoDB)

    Github (and Github actions)

    ElasticSearch

    GraphQL


    Benefits


    Competitive salary

    25 paid vacation days

    8 bank holidays

    5 paid sick days

    SSP

    Work from home flexibility

    Paid parental leave

    Pension program

    Bike storage/shower facilities in building

    Career growth and development opportunities

    This position is not eligible for visa sponsorship.


    Axomic is an Equal Opportunity Employer. We base our employment decisions
    entirely on business needs, job requirements, and qualifications—we do not
    discriminate based on race, gender, religion, health, parental status,
    personal beliefs, veteran status, age, or any other status. We have zero
    tolerance for any kind of discrimination, and we are looking for candidates
    who share those values. Applications from women and members of
    underrepresented minority groups are welcomed.
  example_title: Director of Engineering - Backend Job Description Example
- text: >-
    The Role


    Nesta's Data Science Practice is looking for a Product and Machine Learning
    (ML) Engineer to join our team. Working closely with Nesta's Data Science,
    Software Engineering and Design and Technology teams, the Product and ML
    Engineer will play a key role in increasing the impact of data science
    across Nesta’s 3 missions and BIT, through developing tools, models and data
    into scalable products. This role may suit data scientists with strong
    engineering skills or engineers with a strong machine learning background.


    Key Responsibilities:


    Product development: conceiving, developing, deploying and testing data
    science driven products, including working as part of a multidisciplinary
    team to achieve this.

    Infrastructure development: collaborating with data scientists, data
    engineers and software engineers to create the tools, frameworks and
    infrastructure that enables the acceleration of ML/data driven product
    delivery.

    Opportunity spotting: identifying areas across the organisation that would
    benefit from data science enabled products, and designing solutions to
    achieve impact.

    Scaling up algorithms: building robust, reproducible pipelines, including
    model training, deployment and maintenance.

    Collaboration: Work closely with data scientists, data engineers, analysts
    and other stakeholders to integrate cutting-edge tools and techniques to
    improve the scale and robustness of their work.

    Communication: Understand and articulate trade-offs between different
    solutions and discuss these with relevant stakeholders to decide
    pragmatically between a range of options, taking into account factors such
    as quality, timeliness and impact.

    Standards: taking an active part in establishing ML standards and driving
    quality across our digital and data estate, whilst also coaching and
    upskilling relevant technical staff across the organisation to achieve them.

    Continuous improvement: Stay updated with the latest trends in ML
    engineering to drive the evolution of our platforms.

    Must-Have Skills:


    A minimum of 3 years working in a related technical role (e.g. Data
    Scientist, Data Engineer, Software Developer)

    Experience implementing and deploying machine learning models to be part of
    digital products or research processes.

    Comfortable working with several machine learning frameworks (such as
    PyTorch, scikit-learn, huggingface, spaCy)

    Ability to write code with testability, readability, edge cases and errors
    in mind

    An understanding of software development lifecycles (e.g. system design,
    MLOps architecture)

    Familiarity with engineering and DevOps practices (e.g. CI/CD,
    containerisation)

    Solid understanding of cloud services and systems.

    Version control using Git/Github or equivalent.

    Ability to convert complex data requirements into scalable solutions meeting
    user/stakeholder needs.

    Strong communication skills and proven experience collaborating with a
    diverse range of stakeholders, including non-technical collaborators.

    Experience with agile methodologies and rapid iteration - you have
    experience of iteratively developing software solutions and know when to use
    ML or other approaches to demonstrate user and stakeholder value.

    Nice-to-Haves:


    Previous experience in a research or data-intensive environment.

    Previous experience working in a product focused software development
    environment

    Previous experience developing LLM driven solutions/applications

    Evidence of developing/contributing to open source software

    Experience of working in the public or third sector, or a start-up
    environment.
  example_title: Product and Machine Learning Engineer Job Description Example
- text: >-
    We need a machine learning engineer to work in our growing, dynamic team. We
    are building internal products to help our team perform, execute and excel
    at their job. These tools require us to extract, analyse and infer knowledge
    from our content which help to inform and shape our future content pipeline.


    We are looking for an entrepreneurial mindset to optimise our company’s
    internal and external performance using machine learning capabilities and
    tooling. This will span from building tooling for our teams’ workflows to
    predictive analytics on our vast amounts of video data.


    You must be organised to ensure deadlines are met, and willing to take on
    new challenges. Our work is seen by millions of people each day all around
    the world, so your work will have a massive impact.


    You should be looking for more than just a job. You should aspire to lead
    and own a media company one day as this position holds massive future
    potential for growth.


    As a machine learning engineer, your role will involve:


    Exploring and analysing our data to identify trends and predictive models
    that will optimise our video’s performance;

    Building Interactive Dashboards for Data Visualisation and Analysis.;

    Fine-tuning large language models (e.g. GPT 4), and working with our script
    writers to help us automate parts of our content generation pipeline;

    Working with our team to proactively suggest ways in which technology can be
    applied intelligently to our work pipeline;


    Ideal candidates should demonstrate:


    Creative problem-solving skills, be open-minded and willing to collaborate
    with developers and other members of staff.

    Communication skills to explain complicated solutions to all levels within a
    business.

    A self-starter attitude with a diverse array of interests and a thirst for
    knowledge

    A creative spark with a proven ability to think outside of the box


    You MUST have the following skills:


    Previous experience in building machine learning solutions in a commercial
    setting

    Thorough knowledge of implementing supervised and unsupervised machine
    learning techniques

    Production level Python, including building backends and command line tools

    An enthusiasm for creating and optimising digital media

    Quantitative degree from a top university


    The following is DESIRABLE, not essential:


    Candidates with previous experience with LLM models

    Commercial Experience with Tensorflow / Keras

    Developing cloud native systems

    An enthusiasm for data visualisation and dashboarding


    Benefits:


    Making a serious impact from day one. We're an agile company at the
    forefront of digital content consumption, and your work will impact millions
    of people per day.

    A great office located in Shoreditch right by Old Street Roundabout.

    Competitive salary based on skills and experience

    5 days per week, 9am-6pm with performance-related bonuses

    Social office environment located right by silicon roundabout. Dog friendly,
    with free coffee/tea and regularly scheduled events with other companies
    sharing our building.

    Significant opportunities for growth. We are looking for a senior developer
    to become a key and pivotal part of our team, ample to grow this segment of
    our company and lead others in the future.


    Job Types: Full-time, Permanent


    Pay: From £80,000.00 per year


    Benefits:


    Casual dress

    Company events

    Company pension

    Cycle to work scheme

    Work from home


    Schedule:


    8 hour shift

    Flexitime

    Monday to Friday

    Overtime


    Supplemental pay types:


    Bonus scheme

    Performance bonus


    Education:


    Bachelor's (preferred)


    Work authorisation:


    United Kingdom (required)


    Ability to Commute:


    London (required)


    Ability to Relocate:


    London: Relocate before starting work (required)


    Work Location: Hybrid remote in London
  example_title: Machine Learning Engineer Job Description Example
language:
- en
model-index:
- name: en_pipeline
  results:
  - task:
      name: NER
      type: token-classification
    metrics:
    - name: NER Precision
      type: precision
      value: 0.9006239689
    - name: NER Recall
      type: recall
      value: 1
    - name: NER F Score
      type: f_score
      value: 0.9430596847
library_name: spacy
license: afl-3.0
datasets:
- Etietop/data_analyst_jobs
---
| Feature | Description |
| --- | --- |
| **Name** | `en_pipeline` |
| **Version** | `0.0.0` |
| **spaCy** | `>=3.7.4,<3.8.0` |
| **Default Pipeline** | `tok2vec`, `ner` |
| **Components** | `tok2vec`, `ner` |
| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
| **Sources** | Research at ITMO University. Dataset from Google Search Jobs |
| **License** | Academic Free License |
| **Author** | Etietop Abraham|

### Label Scheme

<details>

<summary>View label scheme (9 labels for 1 components)</summary>

| Component | Labels |
| --- | --- |
| **`ner`** | `Certifications`, `Duties and Responsibilities`, `Education`, `Experience`, `Industry`, `Job Title`, `Skills`, `Soft Skills`, `Tools and Technologies` |

</details>

### Accuracy

| Type | Score |
| --- | --- |
| `ENTS_F` | 94.31 |
| `ENTS_P` | 90.06 |
| `ENTS_R` | 100.00 |
| `TOK2VEC_LOSS` | 483216.60 |
| `NER_LOSS` | 858473.26 |