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Afternoon Mechanical Engineering Machine Learning Jobs in Indiana

V2X

Sr. Principal Mechanical Engineer

Indianapolis, IN · On-site

... machine design and provide mentorship and guidance to engineering teams. You will actively ... Mentor junior engineers and cross-disciplinary teams, fostering a culture of innovation, learning ...

V2X

Sr. Principal Mechanical Engineer

Indianapolis, IN · On-site

... machine design and provide mentorship and guidance to engineering teams. You will actively ... Mentor junior engineers and cross-disciplinary teams, fostering a culture of innovation, learning ...

V2X

Sr. Principal Mechanical Engineer

Indianapolis, IN · On-site

... machine design and provide mentorship and guidance to engineering teams. You will actively ... Mentor junior engineers and cross-disciplinary teams, fostering a culture of innovation, learning ...

V2X

Sr. Principal Mechanical Engineer

Indianapolis, IN · On-site

... machine design and provide mentorship and guidance to engineering teams. You will actively ... Mentor junior engineers and cross-disciplinary teams, fostering a culture of innovation, learning ...

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Afternoon Mechanical Engineering Machine Learning information

What is an afternoon mechanical engineering machine learning job?

An Afternoon Mechanical Engineering Machine Learning job typically refers to a position where professionals apply machine learning techniques to solve problems in mechanical engineering, with working hours scheduled in the afternoon. These roles often involve analyzing engineering data, developing predictive models, and optimizing mechanical systems using advanced algorithms. The work may include tasks such as fault detection, predictive maintenance, or process optimization, leveraging both engineering expertise and machine learning skills. Employees in such positions usually have backgrounds in both mechanical engineering and computer science or data analytics.

What are the key skills and qualifications needed to thrive as an afternoon mechanical engineering machine learning professional?

To excel in this role, you need a solid background in mechanical engineering principles, mathematics, and machine learning concepts, usually supported by a relevant engineering degree. Familiarity with technical tools such as Python, MATLAB, CAD software, and machine learning frameworks (like TensorFlow or scikit-learn) is typically required. Strong analytical thinking, problem-solving, and effective teamwork are valuable soft skills for integrating machine learning with mechanical systems. These competencies are crucial for developing innovative solutions and optimizing engineering processes with data-driven approaches.

How do mechanical engineers specializing in machine learning typically collaborate with other departments during afternoon shifts?

Mechanical engineers working in machine learning often collaborate closely with data scientists, software developers, and production teams, especially during afternoon shifts when testing and implementation often ramp up. They may participate in cross-functional meetings to align on project goals, troubleshoot issues with live data, and refine machine learning models based on feedback from manufacturing or operations staff. This collaborative environment helps ensure that algorithms are practical, efficient, and aligned with real-world applications. Effective communication and adaptability are key, as priorities can shift rapidly based on production needs.

What is the difference between Afternoon Mechanical Engineering Machine Learning vs Afternoon Mechanical Engineering Data Analysis?

AspectAfternoon Mechanical Engineering Machine LearningAfternoon Mechanical Engineering Data Analysis
Required CredentialsBachelor's or Master's in Mechanical Engineering, proficiency in machine learning toolsBachelor's or Master's in Mechanical Engineering, strong data analysis skills
Work EnvironmentResearch labs, tech companies, manufacturing firmsDesign firms, manufacturing plants, research institutions
Employer & Industry UsageTech-driven engineering sectors applying AI/MLTraditional engineering sectors focusing on data interpretation
Search & Comparison IntentUnderstanding roles involving AI/ML in mechanical engineeringComparing data analysis tasks within mechanical engineering

Afternoon Mechanical Engineering Machine Learning focuses on applying AI and machine learning techniques to mechanical engineering problems, often requiring programming and data modeling skills. In contrast, Afternoon Mechanical Engineering Data Analysis emphasizes interpreting and visualizing data to inform engineering decisions. Both roles share foundational engineering knowledge but differ in their technical focus and application areas.

Can mechanical engineers work in machine learning?

Mechanical engineers can work in machine learning by applying their knowledge of systems, modeling, and data analysis to develop algorithms and models for automation, robotics, and predictive maintenance. Gaining skills in programming languages like Python, and understanding data science tools, can facilitate their transition into machine learning roles. Interdisciplinary expertise and additional training in machine learning techniques are often required.

What are the most commonly searched types of Mechanical Engineering Machine Learning jobs in Indiana?

The most popular types of Mechanical Engineering Machine Learning jobs in Indiana are:

Afternoon Mechanical Engineering Machine Learning jobs near you

Machine Learning Engineer New Grad 2024-2025 -Remote

Quora

Evansville, IN • On-site

$139K - $168K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 27 days ago

Job description

About Quora:

Quora’s mission is to grow and share the world’s knowledge. To do so, we have two knowledge sharing products:

  • Quora: a global knowledge sharing platform with over 400M monthly unique visitors, bringing people together to share insights on various topics and providing a unique platform to learn and connect with others.
  • Poe: a platform providing millions of global users with one place to chat, explore and build with a wide variety of AI language models (bots), including o3, o4-mini, Claude 3.7 Sonnet, GPT Image 1 and more. As AI capabilities rapidly advance, Poe provides a single platform to instantly integrate and utilize these new models.

Behind these products are passionate, collaborative, and high-performing global teams. We have a culture rooted in transparency, idea-sharing, and experimentation that allows us to celebrate success and grow together through meaningful work. Join us on this journey to create a positive impact and make a significant change in the world.

This role will be working on our Poe product.

About the Team and Role:

Our small engineering team works on challenging problems every day. We have a culture that's rooted in constantly learning and improving, and our engineers are encouraged to think big and experiment with new ideas. Using continuous deployment, we quickly see our changes in the product and make fast iterations. Our engineers focus on creating polished products and writing high quality code by designing APIs and abstractions that are extensible and maintainable. Everyone on the engineering team has a huge impact on our product and our company.

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code editing, RAG, etc. Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning systems, building performant and reliable LLM applications and collaborating with our product team to uncover new opportunities to the Poe product. You will also play a key role in developing tools and abstractions that our other developers would build on top of.

Responsibilities:
  • Improve our existing Machine Learning systems using your expertise
  • Identify new opportunities to apply Machine Learning to different parts of the Poe product
  • Work with other engineers to implement algorithms and systems in an efficient way
  • Take end-to-end ownership of Machine Learning systems -- from prototyping, data pipelines and training, to realtime LLM application at scale
Minimum Requirements:
  • Ability to be available for meetings and impromptu communication during Quora's “coordination hours" (Mon-Fri: 9am-3pm Pacific Time)
  • A 2024 or 2025 graduate with or pursuing a B.S., M.S., or Ph.D. in Computer Science, Engineering or a related technical field
  • Strong understanding of mathematical foundations of Machine Learning algorithms
  • Experience of transformer models and LLM applications
  • Strong knowledge of Python or C++, or the ability to learn them quickly
  • A passion for learning and always improving yourself and the team around you
Preferred Requirements:
  • Previous software engineering experience via an internship, work experience, or coding competition
  • Previous industry experience working on natural language processing, language modeling, etc.
  • Passion for Quora's mission and goals

At Quora, we value diversity and inclusivity and welcome individuals from all backgrounds, including marginalized or underrepresented groups in tech, to apply for our job openings. We encourage all candidates who share a passion for growing the world’s knowledge, even those who may not strictly meet all the preferred requirements, to apply, as we know that a diverse range of perspectives can have a significant impact on our products and our culture.

Additional Information:

We are accepting applications on an ongoing basis.

Quora offers a wide range of benefits including medical/dental/vision coverage, equity refreshers, remote work reimbursement, paid time off, employee assistance programs, and more. Benefits are country-specific and may vary. For more information on benefits, visit this link: https://www.careers.quora.com/benefits

There are many factors that will determine the starting pay, including but not limited to experience, location, education, and business needs.

  • US candidates only: For US based applicants, the salary range is $107,660 - $161,700 USD + equity + benefits.
  • Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $139,979 - $168,193 CAD + equity + benefits. For all other locations in Canada, the salary range is $130,647 - $156,980 CAD + equity + benefits.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Job Applicant Privacy Notice: https://www.careers.quora.com/applicant-privacy-notice

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