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5 days ago
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Senior Machine Learning Engineer


Salary band: $100k +
Location: North America, United States, Massachusetts
Job type: Permanent
Contact: Cameron Craig
Category: Engineer
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Our successful consumer products client is looking to expand their
core algorithms team by adding a Senior Machine Learning Engineer.
They participate in the full product/feature lifecycle: imagining new
customer-facing features, designing compelling user interfaces,
constructing appropriate software architecture and infrastructure,
implementing compelling proofs of concept, and scaling their
solutions. You will be responsible for the algorithms and models
that underlie the experiences they create. You will apply practical
experience dealing with messy data, your deep understanding of machine
learning fundamentals and algorithms, willingness to write code to
explore problems and understand data, and ability to implement
solutions from scratch, all while solving challenging real-world
problems at large scale.

REQUIREMENTS OF THE SENIOR MACHINE LEARNING ENGINEER:

* MS or ****. in computer science, statistics or related field
* Proven expertise (5+ years) in the fundamentals and practical
application of Machine Learning

* Experience with most of:

* Data manipulation: extensive SQL, Hive QL, Python,
Map-Reduce/Spark
* Statistical modeling packages: Pandas, NumPy, SciPy, StatsModels,
PyMC, Weka
* Time series forecasting, Recommendation engines (collaborative,
content-based filtering, and hybrid systems), and learning-to-rank
algorithms such as RankBoost, LambdaMART
* Machine learning: clustering (hierarchical, K-means, etc.),
decision trees, neural networks, affinity analysis (market basket
analysis), support vector machines
* Predictive modeling: Generalized Linear Models (including but not
limited to multi-linear and Logistic regression), Random Forests,
ensemble learning
* Optimization algorithms such as Stochastic Gradient Descent,
Expectation-Maximization
* Familiarity with using Lucene/SOLR, Elasticsearch or other
Information Retrieval systems
* MapReduce/cluster computing frameworks and libraries such as
Spark, Flink, Mahoot, Hive

* Ability to create prototypes in R, Python, Scala, Java or similar
stack to demonstrate the results of various algorithmic approaches and
evaluate their performance
* Experience working with Big Data, crunching billions of samples
for data mining, statistical modeling, in classification, clustering,
and prediction use-cases
* Demonstrated ability to work effectively in a cross-functional
team

#jobs
#machinelearning
#machinelearningengineer
#dataengineer
#algorithmsengineer
Our successful consumer products client is looking to expand their
core algorithms team by adding a Senior Machine Learning Engineer.
They participate in the full product/feature lifecycle: imagining new
customer-facing features, designing compelling user interfaces,
constructing appropriate software architecture and infrastructure,
implementing compelling proofs of concept, and scaling their
solutions. You will be responsible for the algorithms and models
that underlie the experiences they create. You will apply practical
experience dealing with messy data, your deep understanding of machine
learning fundamentals and algorithms, willingness to write code to
explore problems and understand data, and ability to implement
solutions from scratch, all while solving challenging real-world
problems at large scale.

REQUIREMENTS OF THE SENIOR MACHINE LEARNING ENGINEER:

* MS or ****. in computer science, statistics or related field
* Proven expertise (5+ years) in the fundamentals and practical
application of Machine Learning

* Experience with most of:

* Data manipulation: extensive SQL, Hive QL, Python,
Map-Reduce/Spark
* Statistical modeling packages: Pandas, NumPy, SciPy, StatsModels,
PyMC, Weka
* Time series forecasting, Recommendation engines (collaborative,
content-based filtering, and hybrid systems), and learning-to-rank
algorithms such as RankBoost, LambdaMART
* Machine learning: clustering (hierarchical, K-means, etc.),
decision trees, neural networks, affinity analysis (market basket
analysis), support vector machines
* Predictive modeling: Generalized Linear Models (including but not
limited to multi-linear and Logistic regression), Random Forests,
ensemble learning
* Optimization algorithms such as Stochastic Gradient Descent,
Expectation-Maximization
* Familiarity with using Lucene/SOLR, Elasticsearch or other
Information Retrieval systems
* MapReduce/cluster computing frameworks and libraries such as
Spark, Flink, Mahoot, Hive

* Ability to create prototypes in R, Python, Scala, Java or similar
stack to demonstrate the results of various algorithmic approaches and
evaluate their performance
* Experience working with Big Data, crunching billions of samples
for data mining, statistical modeling, in classification, clustering,
and prediction use-cases
* Demonstrated ability to work effectively in a cross-functional
team

#jobs
#machinelearning
#machinelearningengineer
#dataengineer
#algorithmsengineer

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