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Principal Data Engineer

We are currently recruiting for a Principal Data Engineer to join an exciting Series D startup based in Los Angeles. They sit in the Media space and deal with huge amounts of data from the likes of YouTube.  

They are looking for someone to come at Principal level to drive and build out the data infrastructure.  

You as the ideal candidate will be responsible for:
  • Leading on building and developing ETL processes and data pipelines
  • Working with analytics to develop new tools
  • Automation and orchestration of data pipelines
  • Development data solutions in an AWS environment
  • Mentoring other members of the data team

You as the ideal candidate will require:
  • Experience in a similar fast paced data role
  • Spark experience – Must have
  • AWS experience
  • Strong Python experience
  • Experience with media API’s will be a benefit
 
Salary: $180-210k

If you feel this is a good fit. Please apply or send an updated resume to kieran@alldus.com
 
Our client helps companies ensure the security of their personnel and operations with detailed, street-level threat intelligence. Utilizing AI to aggregate public and proprietary information, they have developed the world’s largest dataset of global threat patterns. Their visualization platform assists companies in conducting geolocation-based analysis for travel safety, threat intelligence, crisis management, site selection, expansion and more.

They are seeking to hire a seasoned Senior Backend Engineer is being sought to tackle technical challenges with prompt, effective solutions. Reporting to the VP of Engineering, the successful candidate will take on responsibilities amid team expansion, collaborating closely with Product, Data Science, Security Analysts, and external contractors to drive the company's success.


Responsibilities
  • As a Senior Backend engineer, you will be responsible for enhancing the Data pipeline platform, API infrastructure, Mapping infrastructure and Automated testing infrastructure.
  • You will be tasked with overseeing and optimizing the backbone of data movement and transformation, ensuring its efficiency and reliability in handling large datasets and workflows.
  • Develop and maintain robust interfaces for seamless communication and interaction between various systems, ensuring smooth data exchange and functionality.
  • Craft and refine the mapping systems integral to the company's operations, enhancing geographical representations and functionalities for better visualization and analysis.
  • Build and refine systems that automate the testing processes, ensuring the reliability and accuracy of the codebase while facilitating rapid and error-free deployments.


Skillset
  • A minimum of five years of experience working in a Backend development role.
  • Proficient in leveraging Node.js within cloud-based architectures.
  • Ability to develop scalable and efficient solutions for diverse backend needs while optimizing performance in cloud environments.
  • Experienced in utilizing collaborative methodologies like Agile, Github, and Jira to streamline development workflows.
  • Extensive experience with AWS, including leveraging Node.js Lambda functions for serverless computing, utilizing S3 for scalable storage, managing infrastructure with ECS, and optimizing solutions for AWS environments.
  • Skilled in developing and deploying applications using Linux-based containers, ensuring compatibility, scalability, and security within containerized environments.


Benefits
Full time remote working (US Based only)
Salary: TBC by client



If this sounds like the role for you, upload your resume via the Apply Now’ link below or send your resume directly to angelo@alldus.com for consideration.

Our client is a dynamic early-stage startup focused on revolutionizing cardiovascular diagnostics through advanced machine learning (ML) algorithms. They are committed to enhancing patient outcomes by leveraging their extensive database of over 200 million individual echo and heart-related images.

 

Job Description:

We are seeking a passionate and talented Computer Vision Engineer, ideally straight out of a Ph.D. program, or early in your career, to join our growing team. The candidate will play a key role in developing and refining ML algorithms to analyze and interpret complex cardiac imagery. This position offers a unique opportunity to contribute to groundbreaking work in medical imaging and improve healthcare delivery.

 

Key Responsibilities:

  1. Develop and optimize machine learning algorithms for analyzing cardiac images.
  2. Collaborate with cross-functional teams to integrate these algorithms into our existing systems.
  3. Conduct thorough testing and validation of algorithms to ensure accuracy and reliability.
  4. Stay updated on the latest developments in computer vision and machine learning, particularly in medical imaging.
  5. Assist in the management and analysis of our extensive image database.
  6. Contribute to research and publish findings in leading scientific journals.

 

Qualifications:

  1. Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field, with a focus on computer vision or machine learning.
  2. Strong programming skills in Python, C++, or similar languages.
  3. Experience with machine learning frameworks such as TensorFlow or PyTorch.
  4. Knowledge of medical imaging and cardiac anatomy is a plus.
  5. Excellent problem-solving and analytical skills.
  6. Strong communication and teamwork abilities.
  7. Demonstrated experience with computer vision/medical imaging, in industry or with academic projects.
Salary: $100-120k
Our client is currently seeking a seasoned individual contributor with a strong background in Large Language Models (LLM) and Generative AI to join our recently established Data Science Lab. In this role, you will be instrumental in crafting advanced data science solutions that leverage the capabilities of machine learning and artificial intelligence, driving innovation across diverse business lines and products at the enterprise level. Collaborating closely with Data Science Tech Leads, you will actively contribute to impactful and highly visible projects, delivering AI/ML solutions that undergo rigorous market testing and deployment, thereby influencing risk management and overall financial performance. Successful candidates will bring industry-specific expertise, a genuine enthusiasm for applying state-of-the-art ML and AI insights, and the ability to design and implement data science capabilities that promote growth, competitive advantage, and customer satisfaction.

Key Responsibilities:
Deep Learning, Large Language Models (LLM), and Generative AI:
  • Extract insights from unstructured data, including insurance contracts, medical records, sales notes, and customer servicing logs.
  • Implement AI/ML solutions, enhancing underwriting risk assessment, claims auto adjudication, and customer servicing.
  • Conduct large-scale experiments, covering unsupervised pre-training, fine-tuning, retrieval augmentation, and prompt engineering.
  • Scale LLM models in both development and production environments.
  • Design and create high-quality prompts and templates guiding LLM behavior, ensuring accuracy, relevance, and language fluency. Optimize prompts for improved user interactions and system performance.
  • Evaluate LLM models using statistical tests, business metrics, and assessments of bias and other regulatory considerations.

Develop Enterprise Test and Learn Capabilities:
  • Investigate current experimentation practices and causal inferencing/ML techniques, identifying opportunities for upscaling methodology best practices.
  • Develop and execute advanced data-driven experiments to optimize various aspects of business operations.
  • Create test hypotheses, design experiments including KPI selection, and collect and analyze data.

Support and Contribute to Building the Data Science Lab (DSL):
  • Assist in use case development, including initial data exploration, project/sample design, data reception and processing, analysis, modeling, and the creation of final reports/presentations.
  • Perform data wrangling, data matching, and ETL processes to explore diverse data sources, gain data expertise, conduct summary analyses, and prepare modeling datasets.
  • Apply advanced statistical and AI/ML techniques to develop high-performing predictive models and conduct creative analyses to address business objectives and partner needs.
  • Identify source data and perform data quality checks in both model/solution development and production.
  • Collaborate with Data Engineers and MLOps in packaging and deploying models/solutions.

Contribute to the Overall Data Science Organization:
  • Collaborate with cross-functional teams, including Data Science, Data Engineering, and Business groups.
  • Contribute to the standardization of Data Science tools, processes, and best practices.
Who You Are:
You have a strong passion for staying at the forefront of technology and are enthusiastic about applying the latest AI/ML algorithms and methodologies.
You are characterized by analytical rigor, intellectual curiosity, and a proven track record of leading the creation and execution of data and analytic solutions to address complex business challenges.
Your satisfaction comes from collaborating with fellow data scientists to tackle challenging problems using AI/ML, and witnessing the successful deployment of solutions in the market, delivering tangible value to the company.
You thrive in working within a multi-disciplinary team, engaging with data engineers, business analysts, software developers, and functional business experts, as well as collaborating with business leaders.

What you will have:
PhD with a minimum of 2 years of experience, or Master's degree with at least 4 years of experience in Statistics, Computer Science, Engineering, Applied Mathematics, or a related field.
  • Possess a minimum of 3 years of hands-on experience in ML modeling and development.
  • Demonstrate strong theoretical foundations in probability and statistics, along with expertise in causal inferencing techniques.
  • Showcase extensive experience in deep learning models, including Large Language Models (LLM) and Natural Language Processing (NLP).
  • Have practical experience with GPU, distributed computing, and the application of parallelism to ML solutions.
  • Exhibit strong programming skills in Python, particularly in PyTorch and/or Tensorflow.
  • Maintain a solid background in algorithms and a diverse range of ML models.
  • Display excellent communication skills and the ability to collaborate cross-functionally with Product, Engineering, and other teams at both leadership and hands-on levels.
  • Possess outstanding analytical and problem-solving abilities, coupled with meticulous attention to detail.
  • Demonstrate proven leadership through providing technical guidance and mentorship to data scientists, as well as strong management skills for monitoring and tracking performance, contributing to enterprise success.
Location:
  • 2-3 Days a week at their NYC location

Salary:
  • Up to $180,000 per year

Our client is currently seeking a seasoned individual contributor with a strong background in Large Language Models (LLM) and Generative AI to join our recently established Data Science Lab. In this role, you will be instrumental in crafting advanced data science solutions that leverage the capabilities of machine learning and artificial intelligence, driving innovation across diverse business lines and products at the enterprise level. Collaborating closely with Data Science Tech Leads, you will actively contribute to impactful and highly visible projects, delivering AI/ML solutions that undergo rigorous market testing and deployment, thereby influencing risk management and overall financial performance. Successful candidates will bring industry-specific expertise, a genuine enthusiasm for applying state-of-the-art ML and AI insights, and the ability to design and implement data science capabilities that promote growth, competitive advantage, and customer satisfaction.

Key Responsibilities:
Develop capabilities in Deep Learning, Large Language Models (LLM), and Generative AI:

  • Design and create high-quality prompts and templates to guide LLM behavior and responses. Craft prompts to extract specific information or control the model's output, ensuring accuracy, relevance, and language fluency. Optimize prompts to enhance user interactions and system performance.
  • Map and mine unstructured data from sources such as insurance contracts, medical records, sales notes, and customer servicing logs.
  • Implement AI/ML solutions, including but not limited to improving underwriting risk assessment, claims auto adjudication, and customer servicing.
  • Conduct large-scale experiments, ranging from unsupervised pre-training to fine-tuning, retrieval augmentation, and prompt engineering.
  • Evaluate LLM models through statistical tests, business metrics, and assessments of bias and other regulatory considerations.
Support and contribute to building the Data Science Lab (DSL):
  • Support the development of use cases, including initial data exploration, project/sample design, data reception and processing, analysis, modeling, and the creation of final reports/presentations.
  • Perform data wrangling, data matching, and ETL processes to explore diverse data sources, gain data expertise, conduct summary analyses, and prepare modeling datasets.
  • Utilize advanced statistical and AI/ML techniques to develop high-performing predictive models and conduct creative analyses to address business objectives and partner needs.
  • Identify source data and conduct data quality checks, both in model/solution development and during production.
  • Collaborate with Data Engineers and MLOps for the packaging and deployment of models/solutions.
Contribute to the overall Data Science organization:
 
  • Collaborate with cross-functional teams comprising Data Science, Data Engineering, and Business groups.
  • Contribute to the standardization of Data Science tools, processes, and best practices.

Who You Are:
You have a strong passion for staying at the forefront of technology and are enthusiastic about applying the latest AI/ML algorithms and methodologies. You are characterized by analytical rigor, intellectual curiosity, and a proven track record of leading the creation and execution of data and analytic solutions to address complex business challenges. Your satisfaction comes from collaborating with fellow data scientists to tackle challenging problems using AI/ML, and witnessing the successful deployment of solutions in the market, delivering tangible value to the company. You thrive in working within a multi-disciplinary team, engaging with data engineers, business analysts, software developers, and functional business experts, as well as collaborating with business leaders.
What you will have:
  • Hold a PhD or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
  • Possess foundational experience in data analysis and statistical modeling.
  • Demonstrate a robust theoretical understanding of probability and statistics.
  • Exhibit expertise in deep learning models, encompassing Large Language Models (LLM), Prompt Engineering, and Natural Language Processing (NLP).
  • Have hands-on proficiency in utilizing GPUs, distributed computing, and implementing parallelism in Machine Learning solutions.
  • Showcase advanced programming skills in Python, with a focus on PyTorch and/or Tensorflow.
  • Possess a solid foundation in algorithms and a diverse range of Machine Learning models.
  • Display excellent communication skills and the ability to collaborate cross-functionally with Product, Engineering, and other teams, both at a leadership and hands-on level.
  • Demonstrate exceptional analytical and problem-solving abilities with meticulous attention to detail.
  • Exhibit proven leadership by providing technical guidance and mentorship to data scientists, coupled with strong management skills for monitoring and tracking performance, contributing to enterprise success.
Location:
  • 2-3 Days a week at their NYC location

Salary:
  • Up to $146,000 per year plus bonus
Our client is looking for an LLM Senior Data Scientist to join a growing team and business capable of collaborating with Social Media influencers and creators.

What You’ll Do
  • You’ll fine-tune and serve LLMs and LLM-based pipelines to the build best-in-class workflow tools for social media influencers and creators, shipping updates and new features weekly
  • You’ll be part of a highly motivated team that operates like a startup within a startup
     
Responsibilities
  • Fine-tune pre-trained language models for generative AI applications.
  • Apply, discover and research techniques to optimize existing LLM training and serving, as well as improving the model quality.
  • Develop and deploy the LLMs for a variety of content generation tasks.
  • Share your discoveries, learnings and results with other modelers in the company working on related projects.
  • Continuously research and stay up-to-date with recent advancements in NLP and large language models, applying novel techniques and methodologies to improve our models.
  • Read all the newsletters and obsess over new industry learnings, startups utilizing LLMs in novel ways, and other ways the real world is utilizing LLMs.
  • Conduct experiments and benchmarking to assess the performance of various model architectures and optimize hyperparameters.
  • Troubleshoot and resolve any issues arising during model training and deployment.
  • Work with product teams to ensure smooth product delivery with high standards, prioritize short-term returns and long-term growth.
     
Who You Are
  • Master’s degree in ML, CS, EE, Statistics, Math, or other applicable field
  • Experience in developing models, model training and tuning optimization and in deploying LLMs like BERT and LLaMA
  • 3+ plus years of experience in developing deep learning models
  • Experience having built products backed by ML/AI
  • Experience with predictive modeling and transfer learning
  • Experience with big-data sets
  • PhD is Preferred.
     
Benefits
  • Medical insurance covered up to 100%
  • Dental & vision insurance
  • 401(k) matching
  • Stock options
  • Complimentary gym access
  • Autonomy and upward mobility