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Junior Ml Engineer Jobs (NOW HIRING)

Prophecy Technologies

Senior AIOps ML Engineer

Los Angeles, CA · On-site

$112K - $154K/yr

Mentor junior ML and data engineers and conduct rigorous design reviews. Required Skills: * AI Agents * Kafka and Streaming technologies (Flink / Spark) * Lakehouse architectures (Delta Lake / Apache ...

VOLT

Junior AI/ML Engineer

San Diego, CA · On-site

$48/hr

As a Junior AI/ML Engineer, you will assist with: * Prototype and deliver generative AI and ML features that speed up engineering workflows and further development of our digital platform. This role ...

ManTech

Junior AI/ML Engineer

Arlington, VA · Remote

$83K - $139K/yr

MANTECH seeks a motivated, career and customer-oriented Junior AI/ML Engineer to join our team. On site at the Pentagon . Responsibilities include, but are not limited to: * Design, build, and ...

ManTech International

Junior AI/ML Engineer

Arlington, VA · On-site

$83K - $139K/yr

MANTECH seeks a motivated, career and customer-oriented Junior AI/ML Engineer to join our team. On site at the Pentagon . Responsibilities include, but are not limited to: * Design, build, and ...

Astiva Health

Jr. AI/ML Engineer

Orange, CA · On-site

$70K - $85K/yr

We are seeking a skilled and adaptable Junior AI/ML Engineer to join our fast-moving team building impactful AI solutions in healthcare. Our work focuses on extracting and interpreting data from ...

Diverse Lynx

Senior AIOps ML Engineer

Woodland Hills, CA · On-site

$110K - $151K/yr

Mentor junior ML and data engineers, and conduct rigorous design reviews for new mart schemas and model architectures Company : Diverse Lynx is a WBENC- and NMSDC-certified partner, helping ...

SS&C

Principal ML Engineer

Waltham, MA · Hybrid

Lead methodology improvements, drive technical standards, and mentor junior engineers across data and ML engineering teams. * Provide production support and ensure site reliability for deployed ML ...

Lyra Health

Senior ML Engineer (ML/AI)

$143K - $197K/yr

Provide technical leadership, conduct thorough code reviews, and mentor junior/mid-level engineers on best practices in software craftsmanship and ML engineering. Qualifications * 6+ years of ...

Lyra Health

Senior ML Engineer (ML/AI)

Charleston, WV · Remote

$143K - $197K/yr

Provide technical leadership, conduct thorough code reviews, and mentor junior/mid-level engineers on best practices in software craftsmanship and ML engineering. Qualifications * 6+ years of ...

Vergence

Senior AI/ML Engineer

Bedford, IN · On-site

$93K - $128K/yr

Develop and prototype AI/ML systems to address mission-specific requirements, including computer ... Proven ability to lead complex technical efforts, mentor junior engineers, and interface with ...

Lucid Motors

Senior AI/ML Engineer

Newark, CA

$117K - $161K/yr

Mentor and guide junior engineers, promoting best practices in ML system design, code quality, experimentation, and model governance. * Stay up to date with emerging trends in AI/ML infrastructure ...

Raas Infotek LLC

Senior AI/ML Engineer

Austin, TX · On-site

$103K - $142K/yr

Mentor junior engineers and provide technical leadership on AI initiatives. * Stay up to date with ... AI/ML or cloud certifications are highly preferred. * Experience in enterprise digital ...

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Junior Ml Engineer information

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$33.5K

$71.8K

$109.5K

How much do junior ml engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for junior ml engineer in the United States is $71,799.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,500.00 and $80,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Junior ML Engineers in their first year on the job?

Junior ML Engineers often encounter challenges such as bridging the gap between academic knowledge and real-world applications, understanding complex data pipelines, and managing large datasets. They may also need to quickly learn company-specific tools and frameworks, as well as adapt to working in cross-functional teams with data scientists, software engineers, and product managers. Seeking mentorship, asking questions, and actively participating in team meetings can help overcome these hurdles and accelerate professional growth.

What are the key skills and qualifications needed to thrive as a Junior ML Engineer, and why are they important?

To thrive as a Junior ML Engineer, you need a strong foundation in programming (especially Python), statistics, and machine learning concepts, typically supported by a degree in computer science or a related field. Familiarity with ML libraries such as TensorFlow or PyTorch, experience with version control systems like Git, and certifications from platforms like Coursera or AWS can be advantageous. Strong problem-solving skills, curiosity, and effective communication help you collaborate with teams and learn quickly. These skills and qualities are essential to efficiently build, test, and deploy machine learning models that drive business value.

What is the difference between Junior ML Engineer vs Data Scientist?

AspectJunior ML EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML frameworksBachelor's or Master's in Data Science, Statistics, or related field; strong analytical skills
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, modeling, interpreting data, creating reports
Employer & Industry UsageTech companies, startups, AI-focused firms

While both roles involve working with data and machine learning, a Junior ML Engineer primarily focuses on building and deploying ML models, often with coding and engineering tasks. A Data Scientist emphasizes data analysis, statistical modeling, and deriving insights. The roles overlap in skills and tools but differ in their core responsibilities and focus areas.

What are Junior ML Engineers?

Junior ML Engineers are entry-level professionals who assist in designing, building, and deploying machine learning models under the supervision of more experienced engineers or data scientists. They typically work on data preprocessing, implementing algorithms, and supporting the maintenance and improvement of ML systems. Junior ML Engineers are expected to have foundational knowledge in programming, mathematics, and machine learning concepts, and they often gain hands-on experience by working on real-world projects as part of a team.
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What cities are hiring for Junior Ml Engineer jobs? Cities with the most Junior Ml Engineer job openings:
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Junior Ml Engineer jobs near you
Infographic showing various Junior Ml Engineer job openings in the United States as of July 2026, with employment types broken down into 81% Full Time, and 19% Contract. Highlights an 74% In-person, 13% Hybrid, and 13% Remote job distribution, with an average salary of $71,799 per year, or $34.5 per hour.
Senior AIOps ML Engineer

Senior AIOps ML Engineer

Prophecy Technologies

Los Angeles, CA • On-site

$112K - $154K/yr

Full-time

Posted 13 days ago

Job description

Role Overview:
The Senior AIOps ML Engineer will be responsible for designing, building, and optimizing a robust Lakehouse architecture for petabyte-scale multi-domain observability data. This role involves developing and deploying advanced machine learning models for AIOps, including streaming anomaly detection, root-cause analysis, and incident forecasting. Key responsibilities also include managing the end-to-end MLOps lifecycle, ensuring data quality and performance, and integrating AIOps insights with incident management platforms. The engineer will also focus on security and compliance observability, collaborating with security teams, and contributing to organizational engineering standards and mentorship.
Key Responsibilities:
  • Lakehouse Architecture & Data Engineering: Design and evolve Lakehouse schema (Delta Lake / Apache Iceberg) for multi-domain observability data at petabyte scale. Build and maintain robust ingestion pipelines from OTel Collector through Kafka to the Lakehouse, ensuring exactly-once semantics and strict schema enforcement. Implement dbt transformation models to generate mart-ready, denormalized fact and dimension tables. Define and enforce data quality contracts and SLAs. Optimize query performance utilizing partitioning strategies, Z-ordering, bloom filters, and materialized views.
  • ML Model Development & AIOps: Design, train, and deploy machine learning models for streaming multivariate anomaly detection, root-cause analysis, and incident forecasting. Build low-latency streaming inference pipelines (Flink / Spark Streaming) for real-time anomaly scoring. Develop sophisticated log intelligence models (clustering, NLP classification, error deduplication). Implement unsupervised and semi-supervised methods for User Experience frustration detection and KPI correlation. Own the ML feature store, managing feature engineering, versioning, and backfill pipelines. Instrument model performance tracking, including drift detection, accuracy monitoring, and automated retraining triggers.
  • AIOps Platform & Productionization: Design and operate the end-to-end AIOps workflow, spanning signal ingestion, feature computation, model inference, alert routing, and auto-remediation hooks. Build high-performance model serving infrastructure supporting real-time REST/gRPC endpoints and async batch scoring with strict p99 latency SLOs. Integrate AIOps insights with incident management platforms (PagerDuty, Opsgenie) and internal runbooks. Define and publish metrics from the Business KPI mart to quantify business impact.
  • Security & Compliance Observability: Partner with the Security team to build the Security mart schema, including threat feed ingestion, UEBA baselines, and CVE correlation pipelines. Train anomalous-access and lateral-movement detection models. Ensure all data handling adheres strictly to data residency requirements, PII masking standards, and audit-log protocols.
  • Collaboration & Engineering Standards: Define telemetry schema contracts with the OTel Instrumentation team. Author ML platform RFCs and contribute actively to observability data model standards. Mentor junior ML and data engineers and conduct rigorous design reviews.

Required Skills:
  • AI Agents
  • Kafka and Streaming technologies (Flink / Spark)
  • Lakehouse architectures (Delta Lake / Apache Iceberg)
  • Machine Learning (Anomaly detection, time-series analysis)
  • Observability tools and concepts (OTel, APM, Logs)
  • MLOps practices (feature store management, drift detection, model retraining)
  • Strong proficiency in SQL and Python

Qualifications:
  • 10+ years of experience in a relevant field.

Apply