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Founding Machine Learning Engineer Jobs in Louisiana

$106.40K - $127.80K/yr

Perform exploratory data analysis (EDA) , feature engineering, and data preprocessing on structured and unstructured datasets. * Develop, train, evaluate, and optimize machine learning and deep ...

Job Requisition ID # 26WD94803 Senior Principal Machine Learning Engineer, ML Platform and Systems Architecture Position Overview The work we do at Autodesk touches nearly every person on the planet.

Job Requisition ID # 26WD97132 26WD97132, Pr incipal Machine Learning Engineer, ML Platform and Systems Architecture French translation to follow!/Traduction francaise a suivre! Position Overview The ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Founding Machine Learning Engineer information

What are the key skills and qualifications needed to thrive as a Founding Machine Learning Engineer, and why are they important?

To thrive as a Founding Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, and data science, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and experience deploying ML models in production are typically required. Strong problem-solving abilities, entrepreneurial mindset, and excellent communication skills set standout candidates apart. These skills and qualities are vital for driving innovation, building scalable solutions from scratch, and collaborating within a fast-paced startup environment.

What are some unique challenges and expectations for a Founding Machine Learning Engineer in an early-stage startup?

As a Founding Machine Learning Engineer, you'll face the unique challenge of building the company's machine learning infrastructure from the ground up, often with limited resources and rapidly evolving requirements. You'll be expected to wear many hats, from designing and deploying models to setting up data pipelines and collaborating closely with product and engineering teams. Your role will also involve making critical decisions about technology stacks and best practices that will shape the company's technical direction. Additionally, you'll have significant influence on the company's culture and have ample opportunities for growth as the team expands.

What is a Founding Machine Learning Engineer?

A Founding Machine Learning Engineer is one of the first technical team members at a startup who specializes in designing, building, and deploying machine learning systems. This role involves working closely with the founders to set the technical direction, build core AI products, and establish best practices for data and model development. In addition to hands-on coding and experimentation, a Founding Machine Learning Engineer often influences product decisions and helps shape the company's engineering culture. The role typically requires a blend of deep technical expertise, startup agility, and a willingness to tackle both high-level strategy and low-level engineering tasks.
What are popular job titles related to Founding Machine Learning Engineer jobs in Louisiana? For Founding Machine Learning Engineer jobs in Louisiana, the most frequently searched job titles are:
What job categories do people searching Founding Machine Learning Engineer jobs in Louisiana look for? The top searched job categories for Founding Machine Learning Engineer jobs in Louisiana are:
What cities in Louisiana are hiring for Founding Machine Learning Engineer jobs? Cities in Louisiana with the most Founding Machine Learning Engineer job openings:
Machine Learning Engineer

$106.40K - $127.80K/yr

Full-time

Posted 9 days ago


Accenture Federal Services rating

8.4

Company rating: 8.4 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

48th of 424 rated business services


Job description

Why Avanade? Because there's literally no place like this

We have two parent companies that give us a strong Microsoft ecosystem with space to be ourselves.People who thrive here are motivated, interested in learning and genuinely have a desire to be the best at what they do. If that sounds like you, then we're the perfect match. You will have the opportunity to utilize the most advanced technology within the Microsoft ecosystem, collaborating with some of the world's largest and most renowned companies, as well as working alongside highly intelligent individuals. This environment allows you to make a significant impact on your career trajectory. If you are looking to enhance your skills and drive transformation within businesses, there is no better place to be.

The EME AI Delivery Hub

AI-and particularly Generative AI-is expected to profoundly impact every company over the coming years. Thanks to Microsoft and Avanade's strategic investments in AI and OpenAI, we are uniquely positioned to help our clients become AI-first organizations.

The EME AI Delivery Hub is an Iberia-based nearshore delivery center serving European and Middle Eastern clients, specialized in end-to-end AI and Advanced Analytics solutions. By joining the Hub, you will be part of a delivery pod working in an agile setup, owning AI initiatives from problem framing and data exploration to model development, deployment, and adoption. You will work closely with clients, guiding them throughout their AI and GenAI transformation journey.

Job Overview

As a Senior Analyst - AI & Data Science, you will design, develop, and deliver AI- and data-driven solutions that help our clients achieve measurable business outcomes. This role combines strong Data Science foundations with hands-on AI engineering, including recent GenAI use cases.

You will work across the full data science lifecycle: data exploration, feature engineering, model development, evaluation, and deployment, while also contributing to modern AI solutions such as LLM-based applications, NLP, computer vision, and predictive analytics, primarily on Microsoft Azure.

Key Role Responsibilities

Day-to-day you will:

  • Design and deliver end-to-end Data Science and AI solutions, from business understanding and data exploration to model deployment and monitoring.
  • Perform exploratory data analysis (EDA), feature engineering, and data preprocessing on structured and unstructured datasets.
  • Develop, train, evaluate, and optimize machine learning and deep learning models, selecting appropriate algorithms and validation strategies.
  • Contribute to Generative AI solutions, including LLM-based applications, prompt engineering, RAG architectures, and applied NLP use cases.
  • Translate business problems into analytical and ML formulations, clearly explaining trade-offs and results to both technical and non-technical stakeholders.
  • Support the preparation of client presentations, demos, and proposals, articulating analytical insights and AI-driven value.
  • Stay up to date with the latest advancements in Data Science, ML, DL, and GenAI, and actively share knowledge within the team.
  • Contribute to reusable assets such as code templates, analytical frameworks, and internal training materials.
  • Collaborate with senior team members and architects to identify opportunities where advanced analytics and AI can transform client operations.

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Key Role Skill & Capability Requirements

Core Skills

  • Strong foundation in Data Science and applied Machine Learning, including supervised and unsupervised learning.
  • Hands-on experience with ML/DL frameworks (e.g., scikit-learn, PyTorch, TensorFlow or equivalent).
  • Solid understanding of model evaluation, validation, and performance metrics.
  • Experience working with structured and unstructured data, including text data for NLP use cases.
  • Proficiency in Python for data analysis and ML development.

AI & GenAI

  • Experience or strong interest in Generative AI, including LLMs, embeddings, prompt engineering, and retrieval-based approaches.
  • Familiarity with NLP, computer vision, forecasting, or optimization use cases is a strong plus.
  • Exposure to Azure AI / Azure Machine Learning / Azure OpenAI is highly valued.

Professional Skills

  • Strong analytical and problem-solving mindset, with the ability to structure ambiguous problems.
  • Ability to communicate insights clearly in English and Spanish, both written and verbal.
  • Comfortable working in agile, client-facing environments.

Preferred Education Background

You likely hold a bachelor's and/or master's degree in computer science, Data Science, Statistics, Mathematics, Physics, Engineering, or a related quantitative field. Equivalent practical experience is also valued.

Preferred Years of Work Experience:

  • 3+ years of applied experience delivering Data Science, Machine Learning, or AI projects in real-world environments.
  • Experience over the last few years may be heavily focused on GenAI, but grounded in solid ML/DL and analytical fundamentals.

What We offer

  • An accelerated and structured training program on Microsoft Azure and AI services.
  • Hands-on exposure to real client projects across computer vision, NLP, forecasting, and GenAI (Azure OpenAI, chatbots, RAG).
  • Continuous learning through certifications, mentoring, and internal communities of practice.

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