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Mid Level Machine Learning Teaching Jobs in California

At least 2 years of industry experience in building and deploying production-level machine learning models. * Deep understanding and practical experience with NLP techniques and frameworks, including ...

At least 2 years of industry experience in building and deploying production-level machine learning models. * Deep understanding and practical experience with NLP techniques and frameworks, including ...

Machine Learning Engineer

San Francisco, CA ยท On-site

$225K - $300K/yr

Mid-training and post-training of foundation models * Novel objectives derived from longitudinal ... We are primarily hiring for senior and staff-level engineers who are comfortable owning critical ...

Machine Learning Engineer

San Francisco, CA ยท On-site +1

$172K - $384K/yr

Develop machine learning systems that generate structured vector graphics (e.g., SVG/JSON ) from ... Seniority level * Seniority levelMid-Senior level Employment type * Employment typeFull-time Job ...

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Mid Level Machine Learning Teaching information

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data analysis, and programming. These positions usually involve leadership responsibilities, extensive experience, and may include stock options or bonuses as part of compensation.

Which 3 jobs will survive AI?

Mid Level Machine Learning Teaching roles are likely to persist as they require specialized knowledge, human interaction, and the ability to adapt to new AI tools. Jobs that involve complex problem-solving, creativity, and emotional intelligence, such as data scientists, AI ethics specialists, and technical trainers, are also expected to remain in demand despite AI advancements.

Will MLE be replaced by AI?

Mid Level Machine Learning Engineers (MLEs) focus on developing, deploying, and maintaining machine learning models, which requires a combination of programming, data analysis, and domain knowledge. While AI automation tools can assist with certain tasks, MLEs are essential for designing complex models, troubleshooting, and ensuring ethical and effective implementation, making complete replacement unlikely in the near term.

What is the difference between Mid Level Machine Learning Teaching vs Data Scientist?

AspectMid Level Machine Learning TeachingData Scientist
Required CredentialsBachelor's or Master's in CS, ML, or related; teaching experienceBachelor's or Master's in CS, Data Science, or related; often requires experience
Work EnvironmentEducational institutions, online platforms, corporate trainingTech companies, finance, healthcare, research labs
Employer & Industry UsageEducational and training sectors, universities, online educationPrivate sector, industry-specific applications, research
Common Search & Comparison IntentUnderstanding teaching roles in ML, educational careersData analysis, modeling, industry applications

Mid Level Machine Learning Teaching focuses on educating students or professionals in ML concepts, often requiring teaching experience and educational credentials. Data Scientists analyze data, build models, and apply ML techniques in industry settings. While both roles involve ML knowledge, teaching emphasizes instruction, whereas data science emphasizes application and analysis.

Can I learn ML in 3 months?

For a mid-level machine learning teaching role, gaining foundational knowledge in machine learning typically requires several months of dedicated study, including understanding algorithms, programming in Python, and working with tools like scikit-learn or TensorFlow. While intensive learning over three months can build basic skills, achieving proficiency suitable for teaching or advanced roles usually takes longer and involves practical experience and project work.
What are popular job titles related to Mid Level Machine Learning Teaching jobs in California? For Mid Level Machine Learning Teaching jobs in California, the most frequently searched job titles are:
What job categories do people searching Mid Level Machine Learning Teaching jobs in California look for? The top searched job categories for Mid Level Machine Learning Teaching jobs in California are:
What cities in California are hiring for Mid Level Machine Learning Teaching jobs? Cities in California with the most Mid Level Machine Learning Teaching job openings:
Infographic showing various Mid Level Machine Learning Teaching job openings in California as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 2% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution.
Software Engineer, Machine Learning

Software Engineer, Machine Learning

Ema

Bodega Bay, CA โ€ข On-site

$135K - $200K/yr

Full-time

Posted 8 days ago


Job description

About Ema

Ema is building the worldโ€™s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs.

We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver and Bangalore, Ema is at the frontier of what Agentic AI can do in production โ€” we ship real systems that run real business processes at scale.

Who You Are

We're looking for innovative and passionate Machine Learning Engineers to join our team. You are someone who loves solving complex problems, enjoys the challenges of working with huge data sets, and has a knack for turning theoretical concepts into practical, scalable solutions. You are a strong team player but also thrive in autonomous environments where your ideas can make a significant impact. You love utilizing machine learning techniques to push the boundaries of what is possible within the realm of Natural Language Processing, Information Retrieval and related spaces. Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact.

You Will

  • Conceptualize, develop, and deploy machine learning models that underpin our NLP, retrieval, ranking, reasoning, dialog and code-generation systems.

  • Implement advanced machine learning algorithms, such as Transformer-based models, reinforcement learning, ensemble learning, and agent-based systems to continually improve the performance of our AI systems.

  • Process and analyze large, complex datasets (structured, semi-structured, and unstructured), and use your findings to inform the development of our models.

  • Work across the complete lifecycle of ML model development, including problem definition, data exploration, feature engineering, model training, validation, and deployment.

  • Implement A/B testing and other statistical methods to validate the effectiveness of models. Ensure the integrity and robustness of ML solutions by developing automated testing and validation processes.

  • Clearly communicate the technical workings and benefits of ML models to both technical and non-technical stakeholders, facilitating understanding and adoption.

Minimum Qualifications

  • A Masterโ€™s degree or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.

  • At least 2 years of industry experience in building and deploying production-level machine learning models.

  • Deep understanding and practical experience with NLP techniques and frameworks, including training and inference of large language models.

  • Deep understanding of any of retrieval, ranking, reinforcement learning, and agent-based systems and experience in how to build them for large systems.

  • Proficiency in Python and experience with ML libraries such as TensorFlow or PyTorch.

Ideally, You'd Have

  • Excellent skills in data processing (SQL, ETL, data warehousing) and experience working with large-scale data systems.

  • Experience with machine learning model lifecycle management tools, and an understanding of MLOps principles and best practices.

  • Familiarity with cloud platforms like GCP or Azure.

  • Familiarity with the latest industry and academic trends in machine learning and AI, and the ability to apply this knowledge to practical projects.

  • Good understanding of software development principles, data structures, and algorithms.

  • Excellent problem-solving skills, attention to detail, and a strong capacity for logical thinking.

  • The ability to work collaboratively in an extremely fast-paced, startup environment.

For California Based Candidates

The standard base salary for this position is $135,000 to $200,000 annually.

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.

Ema Unlimited is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or genetics.