Machine Learning Engineer, AICrete

Salary not provided

Python

Java

Linux

Tensorflow

Pandas

Scikit-Learn

PyTorch

Keras

Keep

Mid level

San Francisco Bay Area

Concrete manufacturing solutions

Job no longer available

Concrete manufacturing solutions

1-20 employees

B2BArtificial IntelligenceSustainabilityManufacturingRoboticsConstruction

Job no longer available

Salary not provided

Python

Java

Linux

Tensorflow

Pandas

Scikit-Learn

PyTorch

Keras

Keep

Mid level

San Francisco Bay Area

1-20 employees

B2BArtificial IntelligenceSustainabilityManufacturingRoboticsConstruction

Company mission

To double profitability of ready-mix and precast concrete producers and reduce their CO2 emissions by up to 35%.

Job

Company

Role

Who you are

Proven experience as a Machine Learning Engineer or similar role
Deep understanding of data structures, data modeling, and software architecture
Strong knowledge of math, probability, statistics, and algorithms
Ability to write robust code in Python, Java, and R
Familiarity with machine learning frameworks (like Keras, TensorFlow, PyTorch, etc.) and libraries (like scikit-learn, pandas, etc.)
Experience in visualizing and manipulating big datasets
Familiarity with Linux
Ability to select hardware to run an ML model with the required latency
Excellent communication skills and ability to work in a team
Outstanding analytical and problem-solving skills
Great attention to details, organizational skills, and an analytical mind
Motivated by achieving goals and willing to learn and get results
Act with integrity, keep commitments, and practice transparency
BS in Computer Science
Master's degree or PhD in Computer Science
Familiarity with Reinforcement Learning
Familiarity with Optimization Methods and Algorithms

What the job involves

Study and transform data science prototypes
Explore and visualize data to gain an understanding of it, identifying differences in data distribution that could affect performance
Supervising the data acquisition process
Verifying data quality and ensuring it via data cleaning
Defining data augmentation pipelines
Design machine learning systems
Research and implement appropriate ML algorithms and tools
Develop machine learning applications according to requirements
Select appropriate datasets and data representation methods
Run machine learning tests and experiments
Perform analysis and hyper-parameter tuning
Train and retain systems when necessary
Extend existing ML libraries and frameworks
Deploying models to production
Keep abreast of developments in the field

Our take

Concrete is the second most consumed substance on earth after water and is responsible for approximately 10% of CO2 emissions globally. AICrete offers the first ‘recipe-as-a-service’ platform that optimizes local materials for cleaner and more cost-effective recipes for concrete.

AICrete empowers concrete producers with the tools to respond to and improve the supply chain issues which have long plagued the trillion-dollar industry. By using AI, the company claims to be able to reduce emissions by up to 35% - ultimately hoping to achieve carbon neutral concrete by 2050 - whilst doubling profit margins for concrete producers. However, some have argued that the use of concrete, however optimized, should be called into question.

Recent funding will go towards expanding AICrete’s paid proof of concept program to several major concrete producers with the aim to illustrate AICrete’s current and potential capabilities. Meanwhile, the company will continue investing in the development of its ambitious software by improving its machine learning models and developing robotic systems to automate data collection.

Kirsty

Company Specialist at Welcome to the Jungle

Company

Funding (2 rounds)

Sep 2024

$5m

SEED

Sep 2022

$4m

SEED

Total funding: $9m

Company benefits

Health insurance (medical, dental, vision, and life)
Equity in a fast-growing startup
Paid time off

Company HQ

Santa Fe, Richmond, CA

Leadership

Dr. Parham Aghdasi

(CEO)

Was a Postdoctoral Scholar at the University of California, Berkeley. Previously served as a Research Scientist Assistant at the University of Texas at Arlington.

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