Model: Etietop/en_pipeline
Author: Etietop
Pipeline: token-classification
Library: spacy
Tags: spacy, token-classification, ner, named entity recognition, job description named entity recognition, en, dataset:Etietop/data_analyst_jobs, license:afl-3.0, model-index, region:us
Card metadata: 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
verified: no, name: NER Recall
type: recall
value: 1
verified: no, name: NER F Score
type: f_score
value: 0.9430596847
verified: no
library_name: spacy
license: afl-3.0
datasets: Etietop/data_analyst_jobs
Likes: 1 | All-time downloads: 315
Created: 2024-05-08 22:36:53