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Associate Artificial Intelligence Machine Learning Jobs in Massachusetts

STR

Machine Learning Engineer

Boston, MA

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML ... and artificial intelligence algorithms and analytics to make sense of the complexity that is ...

CVS Health

Senior Machine Learning Engineer

Wellesley, MA · On-site

$111K - $222K/yr

Architect, design, build, and test end to end pipelines leveraging artificial intelligence, machine learning, reinforcement learning to drive CRM Marketing optimization and automation including ...

STR

Machine Learning Engineer

Woburn, MA · On-site

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML ... and artificial intelligence algorithms and analytics to make sense of the complexity that is ...

STR

Machine Learning Engineer

Woburn, MA

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML ... and artificial intelligence algorithms and analytics to make sense of the complexity that is ...

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Associate Artificial Intelligence Machine Learning information

What does an Associate Artificial Intelligence Machine Learning professional do?

An Associate Artificial Intelligence Machine Learning (AI/ML) professional assists with the development, testing, and deployment of AI and machine learning models. They typically work under the supervision of senior data scientists or machine learning engineers, helping to preprocess data, select algorithms, and evaluate model performance. Their responsibilities may also include writing code, analyzing results, and supporting the integration of models into applications or systems. This entry-level role is ideal for those who have foundational knowledge in AI/ML concepts and are looking to gain practical, hands-on experience in the field.

What are the key skills and qualifications needed to thrive as an Associate Artificial Intelligence Machine Learning professional, and why are they important?

To thrive as an Associate Artificial Intelligence Machine Learning professional, you need a solid background in mathematics, statistics, and computer science, typically with a relevant degree and familiarity with machine learning concepts. Proficiency in programming languages like Python or R, experience with frameworks such as TensorFlow or PyTorch, and knowledge of version control systems are commonly required. Strong problem-solving, analytical thinking, and effective communication skills help differentiate top performers in this role. These skills are crucial for developing accurate models, collaborating with multidisciplinary teams, and driving impactful AI solutions.

What are some common challenges faced by Associate Artificial Intelligence Machine Learning professionals in their first year, and how can they overcome them?

Associate AI/ML professionals often encounter challenges such as understanding complex datasets, adapting to rapidly evolving tools and frameworks, and bridging the gap between theoretical knowledge and practical application. Collaborating closely with senior team members, seeking mentorship, and participating in code reviews are effective ways to overcome these challenges. Additionally, staying updated with industry trends and continuously practicing model building on real-world problems can help associates gain confidence and accelerate their learning curve.

What is the difference between Associate Artificial Intelligence Machine Learning vs Data Scientist?

AspectAssociate Artificial Intelligence Machine LearningData Scientist
Required CredentialsBachelor's in CS, AI, or related; certifications in ML/AIBachelor's/Master's in CS, Statistics, or related; often advanced degrees
Work EnvironmentTech companies, R&D labs, startupsData-driven organizations, consulting firms, tech companies
Employer & Industry UsageAI/ML teams, product developmentData analysis, predictive modeling, business insights
Common Search & ComparisonYesYes

Associate Artificial Intelligence Machine Learning roles focus on developing and implementing AI/ML models, often with entry-level responsibilities. Data Scientists analyze data to extract insights, build predictive models, and support decision-making. While both roles require knowledge of programming and statistics, Data Scientists typically have more advanced degrees and focus on data analysis, whereas Associate AI/ML roles are more specialized in AI/ML model development.

What are the most commonly searched types of Artificial Intelligence Machine Learning jobs in Massachusetts?

The most popular types of Artificial Intelligence Machine Learning jobs in Massachusetts are:

What are popular job titles related to Associate Artificial Intelligence Machine Learning jobs in Massachusetts?

For Associate Artificial Intelligence Machine Learning jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Associate Artificial Intelligence Machine Learning jobs in Massachusetts look for?

The top searched job categories for Associate Artificial Intelligence Machine Learning jobs in Massachusetts are:

What cities in Massachusetts are hiring for Associate Artificial Intelligence Machine Learning jobs?

Cities in Massachusetts with the most Associate Artificial Intelligence Machine Learning job openings:

Associate Artificial Intelligence Machine Learning jobs near you

Machine Learning / Reinforcement Learning Infrastructure Engineer

Eka Robotics

Cambridge, MA • On-site

$118K - $155K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary:
Eka Robotics is on a mission to build intelligence for the physical world through advanced robotics. They are seeking a Reinforcement/Machine Learning Infrastructure Engineer to design, implement, and maintain large-scale model training systems that will enhance their robotics research and deployment efforts.
Responsibilities:
• Own Training Infrastructure: Design, implement, and maintain robust systems for large-scale model training, including job orchestration, scheduling, checkpointing, and experiment tracking.
• Developer Experience & Tooling: Build streamlined, intuitive abstractions for launching, monitoring, debugging, and reproducing experiments, minimizing friction and maximizing productivity for our research teams.
• Scale Distributed Training: Work closely with researchers to reliably scale reinforcement learning and machine learning pipelines across compute clusters.
• Resource Management: Ensure efficient allocation and utilization of cloud-based compute resources while building the foundational systems needed for future scaling.
• Collaborate with Researchers: Partner with the research team to understand their needs, build infrastructure that supports cutting-edge methods, guide best practices for training at scale, and contribute to core JAX model and training code.
Qualifications:
Required:
• BS, MS or higher in Computer Science, Computer Engineering, Machine Learning or a related technical field.
• Strong software engineering fundamentals with a proven track record of building ML training infrastructure, internal developer platforms, or scalable systems.
• Hands-on experience with large-scale training using JAX (preferred), PyTorch, or TensorFlow.
• Familiarity with distributed training, multi-host setups, data pipelines, and managing workloads on cloud platforms or orchestration systems (e.g., Kubernetes, SLURM, GCP, AWS).
• Strong cross-functional communication skills, a deep ownership mindset, and a passion for building tools that improve the developer experience.
• Experience building automated testing pipelines, CI/CD for ML workflows, and custom logging/telemetry stacks.
Preferred:
• Background in robotics, reinforcement learning or other machine learning systems.
• Experience designing abstractions that balance researcher flexibility with system reliability.
Company:
Eka Robotics develops robotics and artificial intelligence systems for physical task automation. Founded in , the company is headquartered in Cambridge, MA, US, , with a team of 11-50 employees. The company is currently Early Stage.

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